Experiments track train and test MSE and RMSE correctly \n Code refactoring

.vscode/tasks.json

@@ -19,7 +19,7 @@
 				"docker-build"
 			],
 			"python": {
-				"file": "air-quality-forecast\\main.py"
+				"file": "air-quality-forecast\\model_development.py"
 			}
 		}
 	]

Dockerfile

@@ -8,6 +8,7 @@ ENV PYTHONDONTWRITEBYTECODE=1
 ENV PYTHONUNBUFFERED=1
 
 # Install pip requirements
+ENV GIT_PYTHON_REFRESH=quiet
 COPY requirements.txt .
 RUN python -m pip install -r requirements.txt
 
@@ -15,9 +16,8 @@ WORKDIR /app
 COPY . /app
 
 # Creates a non-root user with an explicit UID and adds permission to access the /app folder
-# For more info, please refer to https://aka.ms/vscode-docker-python-configure-containers
 RUN adduser -u 5678 --disabled-password --gecos "" appuser && chown -R appuser /app
 USER appuser
 
 # During debugging, this entry point will be overridden. For more information, please refer to https://aka.ms/vscode-docker-python-debug
-CMD ["python", "air-quality-forecast\model_development.py"]
+CMD ["python", "air-quality-forecast/model_development.py"]

air-quality-forecast/model_development.py

@@ -15,7 +15,6 @@ from xgboost import XGBRegressor
 from sklearn.ensemble import RandomForestRegressor
 import yaml
 import os
-import sys
 
 warnings.filterwarnings("ignore")
 
@@ -52,13 +51,29 @@ class RegressorTrainer:
         self._x_test: np.ndarray | None = None
         self._y_test: np.ndarray | None = None
         self._n_iter = n_iter
+        self._current_run = None
 
     def _port_in_use(self, port: int) -> bool:
+        """
+        Check if a port is in use.
+
+        Parameters:
+            port (int): Port to check.
+
+        Returns:
+            bool: True if the port is in use, False otherwise.
+        """
         with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
             # This actually returns an int and not a bool
             return s.connect_ex(("localhost", port)) == 0
 
     def _launch_mlflow_server(self) -> None:
+        """
+        Launch MLflow server at http://127.0.0.1:5000, if not already running.
+
+        If the port is already in use, it will print a message saying so.
+        If there is an error launching the server, it will print the error.
+        """
         port = 5000
         if not self._port_in_use(port):
             try:
@@ -68,8 +83,19 @@ class RegressorTrainer:
                     stderr=subprocess.PIPE,
                 )
                 print(f"MLflow server launched at http://127.0.0.1:{port}")
-            except Exception as e:
-                print("Error launching MLflow server:", e)
+            except Exception:
+                try:
+                    subprocess.Popen(
+                        ["python", "-m", "mlflow", "ui", "--port", str(port)],
+                        stdout=subprocess.PIPE,
+                        stderr=subprocess.PIPE,
+                    )
+                    print(f"MLflow server launched at http://127.0.0.1:{port}")
+                except Exception as e:
+                    print("Error launching MLflow server:", e)
+                    print(
+                        "Both py -m mlflow ui and python -m mlflow ui failed. Please run the server yourself."
+                    )
         else:
             print(f"MLflow server is running at http://127.0.0.1:{port}")
 
@@ -95,7 +121,14 @@ class RegressorTrainer:
         self._y_test = np.array(y_test)
 
     def _setup_mlflow(self) -> None:
-        """Set up MLflow configuration."""
+        """
+        Set up MLflow configuration.
+
+        This method launches the MLflow server, sets the MLflow experiment name and
+        tracking URI, enables system metrics logging, and turns on autologging of
+        metrics and parameters.
+
+        """
         self._launch_mlflow_server()
         mlflow.set_experiment(self._experiment_name)
         mlflow.set_tracking_uri("http://localhost:5000/")
@@ -103,7 +136,18 @@ class RegressorTrainer:
         mlflow.autolog()
 
     def _perform_search(self) -> None:
-        """Perform Bayesian optimization for hyperparameters."""
+        """
+        Perform Bayesian optimization for hyperparameters.
+
+        This method initializes and performs a BayesSearchCV search for the best
+        hyperparameters of the regressor. The search is performed on the training
+        data using a TimeSeriesSplit cross-validation scheme. The best
+        hyperparameters and the corresponding mean squared error are logged to
+        MLflow.
+
+        Raises:
+            ValueError: If training data has not been set. Call `_set_data` first.
+        """
         if self._x_train is None or self._y_train is None:
             raise ValueError("Training data has not been set. Call `_set_data` first.")
 
@@ -121,11 +165,20 @@ class RegressorTrainer:
             verbose=1,  # To display progress
             random_state=RANDOM_SEED,  # Ensures reproducibility
         )
-
         self._bayes_search.fit(self._x_train, self._y_train)
 
+        mlflow.log_params(self._bayes_search.best_params_)
+
+        mlflow.log_metric("Correct Train MSE", -self._bayes_search.best_score_)
+
     def _evaluate_model(self) -> None:
-        """Evaluate the best model on the test data and log metrics."""
+        """
+        Evaluate the best model on the test data and log metrics.
+
+        Raises:
+            ValueError: If test data has not been set. Call `_set_data` first.
+            ValueError: If Bayesian search has not been performed. Call `_perform_search` first.
+        """
         if self._x_test is None or self._y_test is None:
             raise ValueError("Test data has not been set. Call `_set_data` first.")
         if self._bayes_search is None:
@@ -143,12 +196,20 @@ class RegressorTrainer:
             self._y_test, best_regressor.predict(self._x_test)
         )
 
-        print(
-            "Best hyperparameters found by Bayesian optimization:",
-            self._bayes_search.best_params_,
-        )
-        print("Test MSE: ", test_mse)
-        print("Test RMSE: ", test_rmse)
+        mlflow.log_metric("Correct Test MSE", test_mse)
+        mlflow.log_metric("Correct Test RMSE", test_rmse)
+
+    def _optimize_and_evaluate(self):
+        """
+        Perform Bayesian optimization for hyperparameters and evaluate the best model on the test data.
+
+        This method wraps `_perform_search` and `_evaluate_model` in a single MLflow run.
+
+        """
+        with mlflow.start_run():
+            self._perform_search()
+            self._evaluate_model()
+            mlflow.end_run()
 
     def run(
         self,
@@ -157,27 +218,18 @@ class RegressorTrainer:
         x_test: np.ndarray,
         y_test: np.ndarray,
     ) -> None:
+        """
+        Run the Bayesian optimization workflow.
+
+        Parameters:
+            x_train (np.ndarray): Training data features.
+            y_train (np.ndarray): Training data labels.
+            x_test (np.ndarray): Test data features.
+            y_test (np.ndarray): Test data labels.
+        """
         self._set_data(x_train, y_train, x_test, y_test)
         self._setup_mlflow()
-        self._perform_search()
-        self._evaluate_model()
-
-
-def set_path() -> None:
-    """
-    Set the path to include the parent directory of the current file.
-
-    This is needed to import modules from the parent directory.
-
-    Parameters:
-        None
-
-    Returns:
-        None
-    """
-    
-    #parentdir = os.path.dirname(currentdir)
-    #sys.path.insert(0, parentdir)
+        self._optimize_and_evaluate()
 
 
 def run_bayesian_optimization(
@@ -214,24 +266,38 @@ def run_bayesian_optimization(
 
 
 def train_all_models():
+    """
+    Train all models using Bayesian optimization.
+
+    This function is used to train the three models (DecisionTreeRegressor, XGBRegressor, and RandomForestRegressor)
+    using Bayesian optimization.
+
+    The training and test data are loaded from the "data/processed" directory.
+
+    The hyperparameter search spaces for each model are loaded from "configs/hyperparameter_search_spaces.yaml".
+
+    The trained models are logged to the MLflow server.
+
+    """
     np.random.seed(RANDOM_SEED)
 
     project_root = os.path.dirname(os.path.dirname(__file__))
     processed_data_path = os.path.join(project_root, "data", "processed")
-    
 
     x_train, y_train = (
         pd.read_csv(os.path.join(processed_data_path, "x_train.csv"), index_col=0),
-        pd.read_csv(os.path.join(processed_data_path, "y_train.csv"), index_col=0)
+        pd.read_csv(os.path.join(processed_data_path, "y_train.csv"), index_col=0),
     )
     x_test, y_test = (
         pd.read_csv(os.path.join(processed_data_path, "x_test.csv"), index_col=0),
-        pd.read_csv(os.path.join(processed_data_path, "y_test.csv"), index_col=0)
+        pd.read_csv(os.path.join(processed_data_path, "y_test.csv"), index_col=0),
     )
 
     configs_data_path = os.path.join(project_root, "configs")
-    
-    with open(os.path.join(configs_data_path, "hyperparameter_search_spaces.yaml"), "r") as stream:
+
+    with open(
+        os.path.join(configs_data_path, "hyperparameter_search_spaces.yaml"), "r"
+    ) as stream:
         param_space_config = yaml.safe_load(stream)
 
     run_bayesian_optimization(

mlartifacts/149819317988706962/15225421949b40d1a7edf73fbc1c5acc/artifacts/estimator.html

@@ -0,0 +1,415 @@
+
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+    <meta charset="UTF-8"/>
+  </head>
+  <body>
+    <style>#sk-container-id-2 {
+  /* Definition of color scheme common for light and dark mode */
+  --sklearn-color-text: black;
+  --sklearn-color-line: gray;
+  /* Definition of color scheme for unfitted estimators */
+  --sklearn-color-unfitted-level-0: #fff5e6;
+  --sklearn-color-unfitted-level-1: #f6e4d2;
+  --sklearn-color-unfitted-level-2: #ffe0b3;
+  --sklearn-color-unfitted-level-3: chocolate;
+  /* Definition of color scheme for fitted estimators */
+  --sklearn-color-fitted-level-0: #f0f8ff;
+  --sklearn-color-fitted-level-1: #d4ebff;
+  --sklearn-color-fitted-level-2: #b3dbfd;
+  --sklearn-color-fitted-level-3: cornflowerblue;
+
+  /* Specific color for light theme */
+  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
+  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));
+  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
+  --sklearn-color-icon: #696969;
+
+  @media (prefers-color-scheme: dark) {
+    /* Redefinition of color scheme for dark theme */
+    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
+    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));
+    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
+    --sklearn-color-icon: #878787;
+  }
+}
+
+#sk-container-id-2 {
+  color: var(--sklearn-color-text);
+}
+
+#sk-container-id-2 pre {
+  padding: 0;
+}
+
+#sk-container-id-2 input.sk-hidden--visually {
+  border: 0;
+  clip: rect(1px 1px 1px 1px);
+  clip: rect(1px, 1px, 1px, 1px);
+  height: 1px;
+  margin: -1px;
+  overflow: hidden;
+  padding: 0;
+  position: absolute;
+  width: 1px;
+}
+
+#sk-container-id-2 div.sk-dashed-wrapped {
+  border: 1px dashed var(--sklearn-color-line);
+  margin: 0 0.4em 0.5em 0.4em;
+  box-sizing: border-box;
+  padding-bottom: 0.4em;
+  background-color: var(--sklearn-color-background);
+}
+
+#sk-container-id-2 div.sk-container {
+  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`
+     but bootstrap.min.css set `[hidden] { display: none !important; }`
+     so we also need the `!important` here to be able to override the
+     default hidden behavior on the sphinx rendered scikit-learn.org.
+     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */
+  display: inline-block !important;
+  position: relative;
+}
+
+#sk-container-id-2 div.sk-text-repr-fallback {
+  display: none;
+}
+
+div.sk-parallel-item,
+div.sk-serial,
+div.sk-item {
+  /* draw centered vertical line to link estimators */
+  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));
+  background-size: 2px 100%;
+  background-repeat: no-repeat;
+  background-position: center center;
+}
+
+/* Parallel-specific style estimator block */
+
+#sk-container-id-2 div.sk-parallel-item::after {
+  content: "";
+  width: 100%;
+  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);
+  flex-grow: 1;
+}
+
+#sk-container-id-2 div.sk-parallel {
+  display: flex;
+  align-items: stretch;
+  justify-content: center;
+  background-color: var(--sklearn-color-background);
+  position: relative;
+}
+
+#sk-container-id-2 div.sk-parallel-item {
+  display: flex;
+  flex-direction: column;
+}
+
+#sk-container-id-2 div.sk-parallel-item:first-child::after {
+  align-self: flex-end;
+  width: 50%;
+}
+
+#sk-container-id-2 div.sk-parallel-item:last-child::after {
+  align-self: flex-start;
+  width: 50%;
+}
+
+#sk-container-id-2 div.sk-parallel-item:only-child::after {
+  width: 0;
+}
+
+/* Serial-specific style estimator block */
+
+#sk-container-id-2 div.sk-serial {
+  display: flex;
+  flex-direction: column;
+  align-items: center;
+  background-color: var(--sklearn-color-background);
+  padding-right: 1em;
+  padding-left: 1em;
+}
+
+
+/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
+clickable and can be expanded/collapsed.
+- Pipeline and ColumnTransformer use this feature and define the default style
+- Estimators will overwrite some part of the style using the `sk-estimator` class
+*/
+
+/* Pipeline and ColumnTransformer style (default) */
+
+#sk-container-id-2 div.sk-toggleable {
+  /* Default theme specific background. It is overwritten whether we have a
+  specific estimator or a Pipeline/ColumnTransformer */
+  background-color: var(--sklearn-color-background);
+}
+
+/* Toggleable label */
+#sk-container-id-2 label.sk-toggleable__label {
+  cursor: pointer;
+  display: block;
+  width: 100%;
+  margin-bottom: 0;
+  padding: 0.5em;
+  box-sizing: border-box;
+  text-align: center;
+}
+
+#sk-container-id-2 label.sk-toggleable__label-arrow:before {
+  /* Arrow on the left of the label */
+  content: "▸";
+  float: left;
+  margin-right: 0.25em;
+  color: var(--sklearn-color-icon);
+}
+
+#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {
+  color: var(--sklearn-color-text);
+}
+
+/* Toggleable content - dropdown */
+
+#sk-container-id-2 div.sk-toggleable__content {
+  max-height: 0;
+  max-width: 0;
+  overflow: hidden;
+  text-align: left;
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-0);
+}
+
+#sk-container-id-2 div.sk-toggleable__content.fitted {
+  /* fitted */
+  background-color: var(--sklearn-color-fitted-level-0);
+}
+
+#sk-container-id-2 div.sk-toggleable__content pre {
+  margin: 0.2em;
+  border-radius: 0.25em;
+  color: var(--sklearn-color-text);
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-0);
+}
+
+#sk-container-id-2 div.sk-toggleable__content.fitted pre {
+  /* unfitted */
+  background-color: var(--sklearn-color-fitted-level-0);
+}
+
+#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {
+  /* Expand drop-down */
+  max-height: 200px;
+  max-width: 100%;
+  overflow: auto;
+}
+
+#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {
+  content: "▾";
+}
+
+/* Pipeline/ColumnTransformer-specific style */
+
+#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {
+  color: var(--sklearn-color-text);
+  background-color: var(--sklearn-color-unfitted-level-2);
+}
+
+#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
+  background-color: var(--sklearn-color-fitted-level-2);
+}
+
+/* Estimator-specific style */
+
+/* Colorize estimator box */
+#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-2);
+}
+
+#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
+  /* fitted */
+  background-color: var(--sklearn-color-fitted-level-2);
+}
+
+#sk-container-id-2 div.sk-label label.sk-toggleable__label,
+#sk-container-id-2 div.sk-label label {
+  /* The background is the default theme color */
+  color: var(--sklearn-color-text-on-default-background);
+}
+
+/* On hover, darken the color of the background */
+#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {
+  color: var(--sklearn-color-text);
+  background-color: var(--sklearn-color-unfitted-level-2);
+}
+
+/* Label box, darken color on hover, fitted */
+#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {
+  color: var(--sklearn-color-text);
+  background-color: var(--sklearn-color-fitted-level-2);
+}
+
+/* Estimator label */
+
+#sk-container-id-2 div.sk-label label {
+  font-family: monospace;
+  font-weight: bold;
+  display: inline-block;
+  line-height: 1.2em;
+}
+
+#sk-container-id-2 div.sk-label-container {
+  text-align: center;
+}
+
+/* Estimator-specific */
+#sk-container-id-2 div.sk-estimator {
+  font-family: monospace;
+  border: 1px dotted var(--sklearn-color-border-box);
+  border-radius: 0.25em;
+  box-sizing: border-box;
+  margin-bottom: 0.5em;
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-0);
+}
+
+#sk-container-id-2 div.sk-estimator.fitted {
+  /* fitted */
+  background-color: var(--sklearn-color-fitted-level-0);
+}
+
+/* on hover */
+#sk-container-id-2 div.sk-estimator:hover {
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-2);
+}
+
+#sk-container-id-2 div.sk-estimator.fitted:hover {
+  /* fitted */
+  background-color: var(--sklearn-color-fitted-level-2);
+}
+
+/* Specification for estimator info (e.g. "i" and "?") */
+
+/* Common style for "i" and "?" */
+
+.sk-estimator-doc-link,
+a:link.sk-estimator-doc-link,
+a:visited.sk-estimator-doc-link {
+  float: right;
+  font-size: smaller;
+  line-height: 1em;
+  font-family: monospace;
+  background-color: var(--sklearn-color-background);
+  border-radius: 1em;
+  height: 1em;
+  width: 1em;
+  text-decoration: none !important;
+  margin-left: 1ex;
+  /* unfitted */
+  border: var(--sklearn-color-unfitted-level-1) 1pt solid;
+  color: var(--sklearn-color-unfitted-level-1);
+}
+
+.sk-estimator-doc-link.fitted,
+a:link.sk-estimator-doc-link.fitted,
+a:visited.sk-estimator-doc-link.fitted {
+  /* fitted */
+  border: var(--sklearn-color-fitted-level-1) 1pt solid;
+  color: var(--sklearn-color-fitted-level-1);
+}
+
+/* On hover */
+div.sk-estimator:hover .sk-estimator-doc-link:hover,
+.sk-estimator-doc-link:hover,
+div.sk-label-container:hover .sk-estimator-doc-link:hover,
+.sk-estimator-doc-link:hover {
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-3);
+  color: var(--sklearn-color-background);
+  text-decoration: none;
+}
+
+div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
+.sk-estimator-doc-link.fitted:hover,
+div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
+.sk-estimator-doc-link.fitted:hover {
+  /* fitted */
+  background-color: var(--sklearn-color-fitted-level-3);
+  color: var(--sklearn-color-background);
+  text-decoration: none;
+}
+
+/* Span, style for the box shown on hovering the info icon */
+.sk-estimator-doc-link span {
+  display: none;
+  z-index: 9999;
+  position: relative;
+  font-weight: normal;
+  right: .2ex;
+  padding: .5ex;
+  margin: .5ex;
+  width: min-content;
+  min-width: 20ex;
+  max-width: 50ex;
+  color: var(--sklearn-color-text);
+  box-shadow: 2pt 2pt 4pt #999;
+  /* unfitted */
+  background: var(--sklearn-color-unfitted-level-0);
+  border: .5pt solid var(--sklearn-color-unfitted-level-3);
+}
+
+.sk-estimator-doc-link.fitted span {
+  /* fitted */
+  background: var(--sklearn-color-fitted-level-0);
+  border: var(--sklearn-color-fitted-level-3);
+}
+
+.sk-estimator-doc-link:hover span {
+  display: block;
+}
+
+/* "?"-specific style due to the `<a>` HTML tag */
+
+#sk-container-id-2 a.estimator_doc_link {
+  float: right;
+  font-size: 1rem;
+  line-height: 1em;
+  font-family: monospace;
+  background-color: var(--sklearn-color-background);
+  border-radius: 1rem;
+  height: 1rem;
+  width: 1rem;
+  text-decoration: none;
+  /* unfitted */
+  color: var(--sklearn-color-unfitted-level-1);
+  border: var(--sklearn-color-unfitted-level-1) 1pt solid;
+}
+
+#sk-container-id-2 a.estimator_doc_link.fitted {
+  /* fitted */
+  border: var(--sklearn-color-fitted-level-1) 1pt solid;
+  color: var(--sklearn-color-fitted-level-1);
+}
+
+/* On hover */
+#sk-container-id-2 a.estimator_doc_link:hover {
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-3);
+  color: var(--sklearn-color-background);
+  text-decoration: none;
+}
+
+#sk-container-id-2 a.estimator_doc_link.fitted:hover {
+  /* fitted */
+  background-color: var(--sklearn-color-fitted-level-3);
+}
+</style><div id="sk-container-id-2" class="sk-top-container"><div class="sk-text-repr-fallback"><pre>RandomForestRegressor(max_depth=34)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-2" type="checkbox" checked><label for="sk-estimator-id-2" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;&nbsp;RandomForestRegressor<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.5/modules/generated/sklearn.ensemble.RandomForestRegressor.html">?<span>Documentation for RandomForestRegressor</span></a><span class="sk-estimator-doc-link fitted">i<span>Fitted</span></span></label><div class="sk-toggleable__content fitted"><pre>RandomForestRegressor(max_depth=34)</pre></div> </div></div></div></div>
+  </body>
+</html>
+    

mlartifacts/149819317988706962/39324cef8f2443b7b4b77eefe61ef6ca/artifacts/estimator.html

@@ -0,0 +1,415 @@
+
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+    <meta charset="UTF-8"/>
+  </head>
+  <body>
+    <style>#sk-container-id-2 {
+  /* Definition of color scheme common for light and dark mode */
+  --sklearn-color-text: black;
+  --sklearn-color-line: gray;
+  /* Definition of color scheme for unfitted estimators */
+  --sklearn-color-unfitted-level-0: #fff5e6;
+  --sklearn-color-unfitted-level-1: #f6e4d2;
+  --sklearn-color-unfitted-level-2: #ffe0b3;
+  --sklearn-color-unfitted-level-3: chocolate;
+  /* Definition of color scheme for fitted estimators */
+  --sklearn-color-fitted-level-0: #f0f8ff;
+  --sklearn-color-fitted-level-1: #d4ebff;
+  --sklearn-color-fitted-level-2: #b3dbfd;
+  --sklearn-color-fitted-level-3: cornflowerblue;
+
+  /* Specific color for light theme */
+  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
+  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));
+  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
+  --sklearn-color-icon: #696969;
+
+  @media (prefers-color-scheme: dark) {
+    /* Redefinition of color scheme for dark theme */
+    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
+    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));
+    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
+    --sklearn-color-icon: #878787;
+  }
+}
+
+#sk-container-id-2 {
+  color: var(--sklearn-color-text);
+}
+
+#sk-container-id-2 pre {
+  padding: 0;
+}
+
+#sk-container-id-2 input.sk-hidden--visually {
+  border: 0;
+  clip: rect(1px 1px 1px 1px);
+  clip: rect(1px, 1px, 1px, 1px);
+  height: 1px;
+  margin: -1px;
+  overflow: hidden;
+  padding: 0;
+  position: absolute;
+  width: 1px;
+}
+
+#sk-container-id-2 div.sk-dashed-wrapped {
+  border: 1px dashed var(--sklearn-color-line);
+  margin: 0 0.4em 0.5em 0.4em;
+  box-sizing: border-box;
+  padding-bottom: 0.4em;
+  background-color: var(--sklearn-color-background);
+}
+
+#sk-container-id-2 div.sk-container {
+  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`
+     but bootstrap.min.css set `[hidden] { display: none !important; }`
+     so we also need the `!important` here to be able to override the
+     default hidden behavior on the sphinx rendered scikit-learn.org.
+     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */
+  display: inline-block !important;
+  position: relative;
+}
+
+#sk-container-id-2 div.sk-text-repr-fallback {
+  display: none;
+}
+
+div.sk-parallel-item,
+div.sk-serial,
+div.sk-item {
+  /* draw centered vertical line to link estimators */
+  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));
+  background-size: 2px 100%;
+  background-repeat: no-repeat;
+  background-position: center center;
+}
+
+/* Parallel-specific style estimator block */
+
+#sk-container-id-2 div.sk-parallel-item::after {
+  content: "";
+  width: 100%;
+  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);
+  flex-grow: 1;
+}
+
+#sk-container-id-2 div.sk-parallel {
+  display: flex;
+  align-items: stretch;
+  justify-content: center;
+  background-color: var(--sklearn-color-background);
+  position: relative;
+}
+
+#sk-container-id-2 div.sk-parallel-item {
+  display: flex;
+  flex-direction: column;
+}
+
+#sk-container-id-2 div.sk-parallel-item:first-child::after {
+  align-self: flex-end;
+  width: 50%;
+}
+
+#sk-container-id-2 div.sk-parallel-item:last-child::after {
+  align-self: flex-start;
+  width: 50%;
+}
+
+#sk-container-id-2 div.sk-parallel-item:only-child::after {
+  width: 0;
+}
+
+/* Serial-specific style estimator block */
+
+#sk-container-id-2 div.sk-serial {
+  display: flex;
+  flex-direction: column;
+  align-items: center;
+  background-color: var(--sklearn-color-background);
+  padding-right: 1em;
+  padding-left: 1em;
+}
+
+
+/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
+clickable and can be expanded/collapsed.
+- Pipeline and ColumnTransformer use this feature and define the default style
+- Estimators will overwrite some part of the style using the `sk-estimator` class
+*/
+
+/* Pipeline and ColumnTransformer style (default) */
+
+#sk-container-id-2 div.sk-toggleable {
+  /* Default theme specific background. It is overwritten whether we have a
+  specific estimator or a Pipeline/ColumnTransformer */
+  background-color: var(--sklearn-color-background);
+}
+
+/* Toggleable label */
+#sk-container-id-2 label.sk-toggleable__label {
+  cursor: pointer;
+  display: block;
+  width: 100%;
+  margin-bottom: 0;
+  padding: 0.5em;
+  box-sizing: border-box;
+  text-align: center;
+}
+
+#sk-container-id-2 label.sk-toggleable__label-arrow:before {
+  /* Arrow on the left of the label */
+  content: "▸";
+  float: left;
+  margin-right: 0.25em;
+  color: var(--sklearn-color-icon);
+}
+
+#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {
+  color: var(--sklearn-color-text);
+}
+
+/* Toggleable content - dropdown */
+
+#sk-container-id-2 div.sk-toggleable__content {
+  max-height: 0;
+  max-width: 0;
+  overflow: hidden;
+  text-align: left;
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-0);
+}
+
+#sk-container-id-2 div.sk-toggleable__content.fitted {
+  /* fitted */
+  background-color: var(--sklearn-color-fitted-level-0);
+}
+
+#sk-container-id-2 div.sk-toggleable__content pre {
+  margin: 0.2em;
+  border-radius: 0.25em;
+  color: var(--sklearn-color-text);
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-0);
+}
+
+#sk-container-id-2 div.sk-toggleable__content.fitted pre {
+  /* unfitted */
+  background-color: var(--sklearn-color-fitted-level-0);
+}
+
+#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {
+  /* Expand drop-down */
+  max-height: 200px;
+  max-width: 100%;
+  overflow: auto;
+}
+
+#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {
+  content: "▾";
+}
+
+/* Pipeline/ColumnTransformer-specific style */
+
+#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {
+  color: var(--sklearn-color-text);
+  background-color: var(--sklearn-color-unfitted-level-2);
+}
+
+#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
+  background-color: var(--sklearn-color-fitted-level-2);
+}
+
+/* Estimator-specific style */
+
+/* Colorize estimator box */
+#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-2);
+}
+
+#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
+  /* fitted */
+  background-color: var(--sklearn-color-fitted-level-2);
+}
+
+#sk-container-id-2 div.sk-label label.sk-toggleable__label,
+#sk-container-id-2 div.sk-label label {
+  /* The background is the default theme color */
+  color: var(--sklearn-color-text-on-default-background);
+}
+
+/* On hover, darken the color of the background */
+#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {
+  color: var(--sklearn-color-text);
+  background-color: var(--sklearn-color-unfitted-level-2);
+}
+
+/* Label box, darken color on hover, fitted */
+#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {
+  color: var(--sklearn-color-text);
+  background-color: var(--sklearn-color-fitted-level-2);
+}
+
+/* Estimator label */
+
+#sk-container-id-2 div.sk-label label {
+  font-family: monospace;
+  font-weight: bold;
+  display: inline-block;
+  line-height: 1.2em;
+}
+
+#sk-container-id-2 div.sk-label-container {
+  text-align: center;
+}
+
+/* Estimator-specific */
+#sk-container-id-2 div.sk-estimator {
+  font-family: monospace;
+  border: 1px dotted var(--sklearn-color-border-box);
+  border-radius: 0.25em;
+  box-sizing: border-box;
+  margin-bottom: 0.5em;
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-0);
+}
+
+#sk-container-id-2 div.sk-estimator.fitted {
+  /* fitted */
+  background-color: var(--sklearn-color-fitted-level-0);
+}
+
+/* on hover */
+#sk-container-id-2 div.sk-estimator:hover {
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-2);
+}
+
+#sk-container-id-2 div.sk-estimator.fitted:hover {
+  /* fitted */
+  background-color: var(--sklearn-color-fitted-level-2);
+}
+
+/* Specification for estimator info (e.g. "i" and "?") */
+
+/* Common style for "i" and "?" */
+
+.sk-estimator-doc-link,
+a:link.sk-estimator-doc-link,
+a:visited.sk-estimator-doc-link {
+  float: right;
+  font-size: smaller;
+  line-height: 1em;
+  font-family: monospace;
+  background-color: var(--sklearn-color-background);
+  border-radius: 1em;
+  height: 1em;
+  width: 1em;
+  text-decoration: none !important;
+  margin-left: 1ex;
+  /* unfitted */
+  border: var(--sklearn-color-unfitted-level-1) 1pt solid;
+  color: var(--sklearn-color-unfitted-level-1);
+}
+
+.sk-estimator-doc-link.fitted,
+a:link.sk-estimator-doc-link.fitted,
+a:visited.sk-estimator-doc-link.fitted {
+  /* fitted */
+  border: var(--sklearn-color-fitted-level-1) 1pt solid;
+  color: var(--sklearn-color-fitted-level-1);
+}
+
+/* On hover */
+div.sk-estimator:hover .sk-estimator-doc-link:hover,
+.sk-estimator-doc-link:hover,
+div.sk-label-container:hover .sk-estimator-doc-link:hover,
+.sk-estimator-doc-link:hover {
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-3);
+  color: var(--sklearn-color-background);
+  text-decoration: none;
+}
+
+div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
+.sk-estimator-doc-link.fitted:hover,
+div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
+.sk-estimator-doc-link.fitted:hover {
+  /* fitted */
+  background-color: var(--sklearn-color-fitted-level-3);
+  color: var(--sklearn-color-background);
+  text-decoration: none;
+}
+
+/* Span, style for the box shown on hovering the info icon */
+.sk-estimator-doc-link span {
+  display: none;
+  z-index: 9999;
+  position: relative;
+  font-weight: normal;
+  right: .2ex;
+  padding: .5ex;
+  margin: .5ex;
+  width: min-content;
+  min-width: 20ex;
+  max-width: 50ex;
+  color: var(--sklearn-color-text);
+  box-shadow: 2pt 2pt 4pt #999;
+  /* unfitted */
+  background: var(--sklearn-color-unfitted-level-0);
+  border: .5pt solid var(--sklearn-color-unfitted-level-3);
+}
+
+.sk-estimator-doc-link.fitted span {
+  /* fitted */
+  background: var(--sklearn-color-fitted-level-0);
+  border: var(--sklearn-color-fitted-level-3);
+}
+
+.sk-estimator-doc-link:hover span {
+  display: block;
+}
+
+/* "?"-specific style due to the `<a>` HTML tag */
+
+#sk-container-id-2 a.estimator_doc_link {
+  float: right;
+  font-size: 1rem;
+  line-height: 1em;
+  font-family: monospace;
+  background-color: var(--sklearn-color-background);
+  border-radius: 1rem;
+  height: 1rem;
+  width: 1rem;
+  text-decoration: none;
+  /* unfitted */
+  color: var(--sklearn-color-unfitted-level-1);
+  border: var(--sklearn-color-unfitted-level-1) 1pt solid;
+}
+
+#sk-container-id-2 a.estimator_doc_link.fitted {
+  /* fitted */
+  border: var(--sklearn-color-fitted-level-1) 1pt solid;
+  color: var(--sklearn-color-fitted-level-1);
+}
+
+/* On hover */
+#sk-container-id-2 a.estimator_doc_link:hover {
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-3);
+  color: var(--sklearn-color-background);
+  text-decoration: none;
+}
+
+#sk-container-id-2 a.estimator_doc_link.fitted:hover {
+  /* fitted */
+  background-color: var(--sklearn-color-fitted-level-3);
+}
+</style><div id="sk-container-id-2" class="sk-top-container"><div class="sk-text-repr-fallback"><pre>RandomForestRegressor(max_depth=34)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-2" type="checkbox" checked><label for="sk-estimator-id-2" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;&nbsp;RandomForestRegressor<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.5/modules/generated/sklearn.ensemble.RandomForestRegressor.html">?<span>Documentation for RandomForestRegressor</span></a><span class="sk-estimator-doc-link fitted">i<span>Fitted</span></span></label><div class="sk-toggleable__content fitted"><pre>RandomForestRegressor(max_depth=34)</pre></div> </div></div></div></div>
+  </body>
+</html>
+    

mlartifacts/149819317988706962/39324cef8f2443b7b4b77eefe61ef6ca/artifacts/model/MLmodel

@@ -0,0 +1,25 @@
+artifact_path: model
+flavors:
+  python_function:
+    env:
+      conda: conda.yaml
+      virtualenv: python_env.yaml
+    loader_module: mlflow.sklearn
+    model_path: model.pkl
+    predict_fn: predict
+    python_version: 3.11.0
+  sklearn:
+    code: null
+    pickled_model: model.pkl
+    serialization_format: cloudpickle
+    sklearn_version: 1.5.2
+mlflow_version: 2.16.2
+model_size_bytes: 34769333
+model_uuid: 1223b8cf87ee4fae9c34ac54eeef9eb4
+run_id: 39324cef8f2443b7b4b77eefe61ef6ca
+signature:
+  inputs: '[{"type": "tensor", "tensor-spec": {"dtype": "float64", "shape": [-1, 33]}}]'
+  outputs: '[{"type": "tensor", "tensor-spec": {"dtype": "float64", "shape": [-1,
+    6]}}]'
+  params: null
+utc_time_created: '2024-09-30 16:26:16.224496'

mlartifacts/149819317988706962/39324cef8f2443b7b4b77eefe61ef6ca/artifacts/model/conda.yaml

@@ -0,0 +1,15 @@
+channels:
+- conda-forge
+dependencies:
+- python=3.11.0
+- pip<=24.2
+- pip:
+  - mlflow==2.16.2
+  - cloudpickle==3.0.0
+  - numpy==1.26.2
+  - pandas==2.2.2
+  - psutil==5.9.4
+  - scikit-learn==1.5.2
+  - scipy==1.11.4
+  - typing==3.7.4.3
+name: mlflow-env

mlartifacts/149819317988706962/39324cef8f2443b7b4b77eefe61ef6ca/artifacts/model/model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6b51c46f274e74ab79fd748cbe4fa01c5216d66f347bd96f71cfedf31015152f
+size 34769333

mlartifacts/149819317988706962/39324cef8f2443b7b4b77eefe61ef6ca/artifacts/model/python_env.yaml

@@ -0,0 +1,7 @@
+python: 3.11.0
+build_dependencies:
+- pip==24.2
+- setuptools==65.5.0
+- wheel==0.41.2
+dependencies:
+- -r requirements.txt

mlartifacts/149819317988706962/39324cef8f2443b7b4b77eefe61ef6ca/artifacts/model/requirements.txt

@@ -0,0 +1,8 @@
+mlflow==2.16.2
+cloudpickle==3.0.0
+numpy==1.26.2
+pandas==2.2.2
+psutil==5.9.4
+scikit-learn==1.5.2
+scipy==1.11.4
+typing==3.7.4.3

mlartifacts/149819317988706962/faa3ad4458c7419a8fc7c85d44b5c475/artifacts/estimator.html

@@ -0,0 +1,415 @@
+
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+    <meta charset="UTF-8"/>
+  </head>
+  <body>
+    <style>#sk-container-id-2 {
+  /* Definition of color scheme common for light and dark mode */
+  --sklearn-color-text: black;
+  --sklearn-color-line: gray;
+  /* Definition of color scheme for unfitted estimators */
+  --sklearn-color-unfitted-level-0: #fff5e6;
+  --sklearn-color-unfitted-level-1: #f6e4d2;
+  --sklearn-color-unfitted-level-2: #ffe0b3;
+  --sklearn-color-unfitted-level-3: chocolate;
+  /* Definition of color scheme for fitted estimators */
+  --sklearn-color-fitted-level-0: #f0f8ff;
+  --sklearn-color-fitted-level-1: #d4ebff;
+  --sklearn-color-fitted-level-2: #b3dbfd;
+  --sklearn-color-fitted-level-3: cornflowerblue;
+
+  /* Specific color for light theme */
+  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
+  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));
+  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
+  --sklearn-color-icon: #696969;
+
+  @media (prefers-color-scheme: dark) {
+    /* Redefinition of color scheme for dark theme */
+    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
+    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));
+    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
+    --sklearn-color-icon: #878787;
+  }
+}
+
+#sk-container-id-2 {
+  color: var(--sklearn-color-text);
+}
+
+#sk-container-id-2 pre {
+  padding: 0;
+}
+
+#sk-container-id-2 input.sk-hidden--visually {
+  border: 0;
+  clip: rect(1px 1px 1px 1px);
+  clip: rect(1px, 1px, 1px, 1px);
+  height: 1px;
+  margin: -1px;
+  overflow: hidden;
+  padding: 0;
+  position: absolute;
+  width: 1px;
+}
+
+#sk-container-id-2 div.sk-dashed-wrapped {
+  border: 1px dashed var(--sklearn-color-line);
+  margin: 0 0.4em 0.5em 0.4em;
+  box-sizing: border-box;
+  padding-bottom: 0.4em;
+  background-color: var(--sklearn-color-background);
+}
+
+#sk-container-id-2 div.sk-container {
+  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`
+     but bootstrap.min.css set `[hidden] { display: none !important; }`
+     so we also need the `!important` here to be able to override the
+     default hidden behavior on the sphinx rendered scikit-learn.org.
+     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */
+  display: inline-block !important;
+  position: relative;
+}
+
+#sk-container-id-2 div.sk-text-repr-fallback {
+  display: none;
+}
+
+div.sk-parallel-item,
+div.sk-serial,
+div.sk-item {
+  /* draw centered vertical line to link estimators */
+  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));
+  background-size: 2px 100%;
+  background-repeat: no-repeat;
+  background-position: center center;
+}
+
+/* Parallel-specific style estimator block */
+
+#sk-container-id-2 div.sk-parallel-item::after {
+  content: "";
+  width: 100%;
+  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);
+  flex-grow: 1;
+}
+
+#sk-container-id-2 div.sk-parallel {
+  display: flex;
+  align-items: stretch;
+  justify-content: center;
+  background-color: var(--sklearn-color-background);
+  position: relative;
+}
+
+#sk-container-id-2 div.sk-parallel-item {
+  display: flex;
+  flex-direction: column;
+}
+
+#sk-container-id-2 div.sk-parallel-item:first-child::after {
+  align-self: flex-end;
+  width: 50%;
+}
+
+#sk-container-id-2 div.sk-parallel-item:last-child::after {
+  align-self: flex-start;
+  width: 50%;
+}
+
+#sk-container-id-2 div.sk-parallel-item:only-child::after {
+  width: 0;
+}
+
+/* Serial-specific style estimator block */
+
+#sk-container-id-2 div.sk-serial {
+  display: flex;
+  flex-direction: column;
+  align-items: center;
+  background-color: var(--sklearn-color-background);
+  padding-right: 1em;
+  padding-left: 1em;
+}
+
+
+/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
+clickable and can be expanded/collapsed.
+- Pipeline and ColumnTransformer use this feature and define the default style
+- Estimators will overwrite some part of the style using the `sk-estimator` class
+*/
+
+/* Pipeline and ColumnTransformer style (default) */
+
+#sk-container-id-2 div.sk-toggleable {
+  /* Default theme specific background. It is overwritten whether we have a
+  specific estimator or a Pipeline/ColumnTransformer */
+  background-color: var(--sklearn-color-background);
+}
+
+/* Toggleable label */
+#sk-container-id-2 label.sk-toggleable__label {
+  cursor: pointer;
+  display: block;
+  width: 100%;
+  margin-bottom: 0;
+  padding: 0.5em;
+  box-sizing: border-box;
+  text-align: center;
+}
+
+#sk-container-id-2 label.sk-toggleable__label-arrow:before {
+  /* Arrow on the left of the label */
+  content: "▸";
+  float: left;
+  margin-right: 0.25em;
+  color: var(--sklearn-color-icon);
+}
+
+#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {
+  color: var(--sklearn-color-text);
+}
+
+/* Toggleable content - dropdown */
+
+#sk-container-id-2 div.sk-toggleable__content {
+  max-height: 0;
+  max-width: 0;
+  overflow: hidden;
+  text-align: left;
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-0);
+}
+
+#sk-container-id-2 div.sk-toggleable__content.fitted {
+  /* fitted */
+  background-color: var(--sklearn-color-fitted-level-0);
+}
+
+#sk-container-id-2 div.sk-toggleable__content pre {
+  margin: 0.2em;
+  border-radius: 0.25em;
+  color: var(--sklearn-color-text);
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-0);
+}
+
+#sk-container-id-2 div.sk-toggleable__content.fitted pre {
+  /* unfitted */
+  background-color: var(--sklearn-color-fitted-level-0);
+}
+
+#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {
+  /* Expand drop-down */
+  max-height: 200px;
+  max-width: 100%;
+  overflow: auto;
+}
+
+#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {
+  content: "▾";
+}
+
+/* Pipeline/ColumnTransformer-specific style */
+
+#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {
+  color: var(--sklearn-color-text);
+  background-color: var(--sklearn-color-unfitted-level-2);
+}
+
+#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
+  background-color: var(--sklearn-color-fitted-level-2);
+}
+
+/* Estimator-specific style */
+
+/* Colorize estimator box */
+#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-2);
+}
+
+#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
+  /* fitted */
+  background-color: var(--sklearn-color-fitted-level-2);
+}
+
+#sk-container-id-2 div.sk-label label.sk-toggleable__label,
+#sk-container-id-2 div.sk-label label {
+  /* The background is the default theme color */
+  color: var(--sklearn-color-text-on-default-background);
+}
+
+/* On hover, darken the color of the background */
+#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {
+  color: var(--sklearn-color-text);
+  background-color: var(--sklearn-color-unfitted-level-2);
+}
+
+/* Label box, darken color on hover, fitted */
+#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {
+  color: var(--sklearn-color-text);
+  background-color: var(--sklearn-color-fitted-level-2);
+}
+
+/* Estimator label */
+
+#sk-container-id-2 div.sk-label label {
+  font-family: monospace;
+  font-weight: bold;
+  display: inline-block;
+  line-height: 1.2em;
+}
+
+#sk-container-id-2 div.sk-label-container {
+  text-align: center;
+}
+
+/* Estimator-specific */
+#sk-container-id-2 div.sk-estimator {
+  font-family: monospace;
+  border: 1px dotted var(--sklearn-color-border-box);
+  border-radius: 0.25em;
+  box-sizing: border-box;
+  margin-bottom: 0.5em;
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-0);
+}
+
+#sk-container-id-2 div.sk-estimator.fitted {
+  /* fitted */
+  background-color: var(--sklearn-color-fitted-level-0);
+}
+
+/* on hover */
+#sk-container-id-2 div.sk-estimator:hover {
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-2);
+}
+
+#sk-container-id-2 div.sk-estimator.fitted:hover {
+  /* fitted */
+  background-color: var(--sklearn-color-fitted-level-2);
+}
+
+/* Specification for estimator info (e.g. "i" and "?") */
+
+/* Common style for "i" and "?" */
+
+.sk-estimator-doc-link,
+a:link.sk-estimator-doc-link,
+a:visited.sk-estimator-doc-link {
+  float: right;
+  font-size: smaller;
+  line-height: 1em;
+  font-family: monospace;
+  background-color: var(--sklearn-color-background);
+  border-radius: 1em;
+  height: 1em;
+  width: 1em;
+  text-decoration: none !important;
+  margin-left: 1ex;
+  /* unfitted */
+  border: var(--sklearn-color-unfitted-level-1) 1pt solid;
+  color: var(--sklearn-color-unfitted-level-1);
+}
+
+.sk-estimator-doc-link.fitted,
+a:link.sk-estimator-doc-link.fitted,
+a:visited.sk-estimator-doc-link.fitted {
+  /* fitted */
+  border: var(--sklearn-color-fitted-level-1) 1pt solid;
+  color: var(--sklearn-color-fitted-level-1);
+}
+
+/* On hover */
+div.sk-estimator:hover .sk-estimator-doc-link:hover,
+.sk-estimator-doc-link:hover,
+div.sk-label-container:hover .sk-estimator-doc-link:hover,
+.sk-estimator-doc-link:hover {
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-3);
+  color: var(--sklearn-color-background);
+  text-decoration: none;
+}
+
+div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
+.sk-estimator-doc-link.fitted:hover,
+div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
+.sk-estimator-doc-link.fitted:hover {
+  /* fitted */
+  background-color: var(--sklearn-color-fitted-level-3);
+  color: var(--sklearn-color-background);
+  text-decoration: none;
+}
+
+/* Span, style for the box shown on hovering the info icon */
+.sk-estimator-doc-link span {
+  display: none;
+  z-index: 9999;
+  position: relative;
+  font-weight: normal;
+  right: .2ex;
+  padding: .5ex;
+  margin: .5ex;
+  width: min-content;
+  min-width: 20ex;
+  max-width: 50ex;
+  color: var(--sklearn-color-text);
+  box-shadow: 2pt 2pt 4pt #999;
+  /* unfitted */
+  background: var(--sklearn-color-unfitted-level-0);
+  border: .5pt solid var(--sklearn-color-unfitted-level-3);
+}
+
+.sk-estimator-doc-link.fitted span {
+  /* fitted */
+  background: var(--sklearn-color-fitted-level-0);
+  border: var(--sklearn-color-fitted-level-3);
+}
+
+.sk-estimator-doc-link:hover span {
+  display: block;
+}
+
+/* "?"-specific style due to the `<a>` HTML tag */
+
+#sk-container-id-2 a.estimator_doc_link {
+  float: right;
+  font-size: 1rem;
+  line-height: 1em;
+  font-family: monospace;
+  background-color: var(--sklearn-color-background);
+  border-radius: 1rem;
+  height: 1rem;
+  width: 1rem;
+  text-decoration: none;
+  /* unfitted */
+  color: var(--sklearn-color-unfitted-level-1);
+  border: var(--sklearn-color-unfitted-level-1) 1pt solid;
+}
+
+#sk-container-id-2 a.estimator_doc_link.fitted {
+  /* fitted */
+  border: var(--sklearn-color-fitted-level-1) 1pt solid;
+  color: var(--sklearn-color-fitted-level-1);
+}
+
+/* On hover */
+#sk-container-id-2 a.estimator_doc_link:hover {
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-3);
+  color: var(--sklearn-color-background);
+  text-decoration: none;
+}
+
+#sk-container-id-2 a.estimator_doc_link.fitted:hover {
+  /* fitted */
+  background-color: var(--sklearn-color-fitted-level-3);
+}
+</style><div id="sk-container-id-2" class="sk-top-container"><div class="sk-text-repr-fallback"><pre>RandomForestRegressor(max_depth=34)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-2" type="checkbox" checked><label for="sk-estimator-id-2" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;&nbsp;RandomForestRegressor<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.5/modules/generated/sklearn.ensemble.RandomForestRegressor.html">?<span>Documentation for RandomForestRegressor</span></a><span class="sk-estimator-doc-link fitted">i<span>Fitted</span></span></label><div class="sk-toggleable__content fitted"><pre>RandomForestRegressor(max_depth=34)</pre></div> </div></div></div></div>
+  </body>
+</html>
+    

mlartifacts/149819317988706962/faa3ad4458c7419a8fc7c85d44b5c475/artifacts/model/MLmodel

@@ -0,0 +1,25 @@
+artifact_path: model
+flavors:
+  python_function:
+    env:
+      conda: conda.yaml
+      virtualenv: python_env.yaml
+    loader_module: mlflow.sklearn
+    model_path: model.pkl
+    predict_fn: predict
+    python_version: 3.11.0
+  sklearn:
+    code: null
+    pickled_model: model.pkl
+    serialization_format: cloudpickle
+    sklearn_version: 1.5.2
+mlflow_version: 2.16.2
+model_size_bytes: 34769333
+model_uuid: 120c266f00cf4e34aca4337b65a1e372
+run_id: faa3ad4458c7419a8fc7c85d44b5c475
+signature:
+  inputs: '[{"type": "tensor", "tensor-spec": {"dtype": "float64", "shape": [-1, 33]}}]'
+  outputs: '[{"type": "tensor", "tensor-spec": {"dtype": "float64", "shape": [-1,
+    6]}}]'
+  params: null
+utc_time_created: '2024-09-30 11:43:18.288700'

mlartifacts/149819317988706962/faa3ad4458c7419a8fc7c85d44b5c475/artifacts/model/conda.yaml

@@ -0,0 +1,15 @@
+channels:
+- conda-forge
+dependencies:
+- python=3.11.0
+- pip<=24.2
+- pip:
+  - mlflow==2.16.2
+  - cloudpickle==3.0.0
+  - numpy==1.26.2
+  - pandas==2.2.2
+  - psutil==5.9.4
+  - scikit-learn==1.5.2
+  - scipy==1.11.4
+  - typing==3.7.4.3
+name: mlflow-env

mlartifacts/149819317988706962/faa3ad4458c7419a8fc7c85d44b5c475/artifacts/model/model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6b51c46f274e74ab79fd748cbe4fa01c5216d66f347bd96f71cfedf31015152f
+size 34769333

mlartifacts/149819317988706962/faa3ad4458c7419a8fc7c85d44b5c475/artifacts/model/python_env.yaml

@@ -0,0 +1,7 @@
+python: 3.11.0
+build_dependencies:
+- pip==24.2
+- setuptools==65.5.0
+- wheel==0.41.2
+dependencies:
+- -r requirements.txt

mlartifacts/149819317988706962/faa3ad4458c7419a8fc7c85d44b5c475/artifacts/model/requirements.txt

@@ -0,0 +1,8 @@
+mlflow==2.16.2
+cloudpickle==3.0.0
+numpy==1.26.2
+pandas==2.2.2
+psutil==5.9.4
+scikit-learn==1.5.2
+scipy==1.11.4
+typing==3.7.4.3

mlartifacts/149819317988706962/ff9b209269104b37b82bb9564fe96907/artifacts/estimator.html

@@ -0,0 +1,415 @@
+
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+    <meta charset="UTF-8"/>
+  </head>
+  <body>
+    <style>#sk-container-id-2 {
+  /* Definition of color scheme common for light and dark mode */
+  --sklearn-color-text: black;
+  --sklearn-color-line: gray;
+  /* Definition of color scheme for unfitted estimators */
+  --sklearn-color-unfitted-level-0: #fff5e6;
+  --sklearn-color-unfitted-level-1: #f6e4d2;
+  --sklearn-color-unfitted-level-2: #ffe0b3;
+  --sklearn-color-unfitted-level-3: chocolate;
+  /* Definition of color scheme for fitted estimators */
+  --sklearn-color-fitted-level-0: #f0f8ff;
+  --sklearn-color-fitted-level-1: #d4ebff;
+  --sklearn-color-fitted-level-2: #b3dbfd;
+  --sklearn-color-fitted-level-3: cornflowerblue;
+
+  /* Specific color for light theme */
+  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
+  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));
+  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));
+  --sklearn-color-icon: #696969;
+
+  @media (prefers-color-scheme: dark) {
+    /* Redefinition of color scheme for dark theme */
+    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
+    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));
+    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));
+    --sklearn-color-icon: #878787;
+  }
+}
+
+#sk-container-id-2 {
+  color: var(--sklearn-color-text);
+}
+
+#sk-container-id-2 pre {
+  padding: 0;
+}
+
+#sk-container-id-2 input.sk-hidden--visually {
+  border: 0;
+  clip: rect(1px 1px 1px 1px);
+  clip: rect(1px, 1px, 1px, 1px);
+  height: 1px;
+  margin: -1px;
+  overflow: hidden;
+  padding: 0;
+  position: absolute;
+  width: 1px;
+}
+
+#sk-container-id-2 div.sk-dashed-wrapped {
+  border: 1px dashed var(--sklearn-color-line);
+  margin: 0 0.4em 0.5em 0.4em;
+  box-sizing: border-box;
+  padding-bottom: 0.4em;
+  background-color: var(--sklearn-color-background);
+}
+
+#sk-container-id-2 div.sk-container {
+  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`
+     but bootstrap.min.css set `[hidden] { display: none !important; }`
+     so we also need the `!important` here to be able to override the
+     default hidden behavior on the sphinx rendered scikit-learn.org.
+     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */
+  display: inline-block !important;
+  position: relative;
+}
+
+#sk-container-id-2 div.sk-text-repr-fallback {
+  display: none;
+}
+
+div.sk-parallel-item,
+div.sk-serial,
+div.sk-item {
+  /* draw centered vertical line to link estimators */
+  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));
+  background-size: 2px 100%;
+  background-repeat: no-repeat;
+  background-position: center center;
+}
+
+/* Parallel-specific style estimator block */
+
+#sk-container-id-2 div.sk-parallel-item::after {
+  content: "";
+  width: 100%;
+  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);
+  flex-grow: 1;
+}
+
+#sk-container-id-2 div.sk-parallel {
+  display: flex;
+  align-items: stretch;
+  justify-content: center;
+  background-color: var(--sklearn-color-background);
+  position: relative;
+}
+
+#sk-container-id-2 div.sk-parallel-item {
+  display: flex;
+  flex-direction: column;
+}
+
+#sk-container-id-2 div.sk-parallel-item:first-child::after {
+  align-self: flex-end;
+  width: 50%;
+}
+
+#sk-container-id-2 div.sk-parallel-item:last-child::after {
+  align-self: flex-start;
+  width: 50%;
+}
+
+#sk-container-id-2 div.sk-parallel-item:only-child::after {
+  width: 0;
+}
+
+/* Serial-specific style estimator block */
+
+#sk-container-id-2 div.sk-serial {
+  display: flex;
+  flex-direction: column;
+  align-items: center;
+  background-color: var(--sklearn-color-background);
+  padding-right: 1em;
+  padding-left: 1em;
+}
+
+
+/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is
+clickable and can be expanded/collapsed.
+- Pipeline and ColumnTransformer use this feature and define the default style
+- Estimators will overwrite some part of the style using the `sk-estimator` class
+*/
+
+/* Pipeline and ColumnTransformer style (default) */
+
+#sk-container-id-2 div.sk-toggleable {
+  /* Default theme specific background. It is overwritten whether we have a
+  specific estimator or a Pipeline/ColumnTransformer */
+  background-color: var(--sklearn-color-background);
+}
+
+/* Toggleable label */
+#sk-container-id-2 label.sk-toggleable__label {
+  cursor: pointer;
+  display: block;
+  width: 100%;
+  margin-bottom: 0;
+  padding: 0.5em;
+  box-sizing: border-box;
+  text-align: center;
+}
+
+#sk-container-id-2 label.sk-toggleable__label-arrow:before {
+  /* Arrow on the left of the label */
+  content: "▸";
+  float: left;
+  margin-right: 0.25em;
+  color: var(--sklearn-color-icon);
+}
+
+#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {
+  color: var(--sklearn-color-text);
+}
+
+/* Toggleable content - dropdown */
+
+#sk-container-id-2 div.sk-toggleable__content {
+  max-height: 0;
+  max-width: 0;
+  overflow: hidden;
+  text-align: left;
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-0);
+}
+
+#sk-container-id-2 div.sk-toggleable__content.fitted {
+  /* fitted */
+  background-color: var(--sklearn-color-fitted-level-0);
+}
+
+#sk-container-id-2 div.sk-toggleable__content pre {
+  margin: 0.2em;
+  border-radius: 0.25em;
+  color: var(--sklearn-color-text);
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-0);
+}
+
+#sk-container-id-2 div.sk-toggleable__content.fitted pre {
+  /* unfitted */
+  background-color: var(--sklearn-color-fitted-level-0);
+}
+
+#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {
+  /* Expand drop-down */
+  max-height: 200px;
+  max-width: 100%;
+  overflow: auto;
+}
+
+#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {
+  content: "▾";
+}
+
+/* Pipeline/ColumnTransformer-specific style */
+
+#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {
+  color: var(--sklearn-color-text);
+  background-color: var(--sklearn-color-unfitted-level-2);
+}
+
+#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
+  background-color: var(--sklearn-color-fitted-level-2);
+}
+
+/* Estimator-specific style */
+
+/* Colorize estimator box */
+#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-2);
+}
+
+#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {
+  /* fitted */
+  background-color: var(--sklearn-color-fitted-level-2);
+}
+
+#sk-container-id-2 div.sk-label label.sk-toggleable__label,
+#sk-container-id-2 div.sk-label label {
+  /* The background is the default theme color */
+  color: var(--sklearn-color-text-on-default-background);
+}
+
+/* On hover, darken the color of the background */
+#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {
+  color: var(--sklearn-color-text);
+  background-color: var(--sklearn-color-unfitted-level-2);
+}
+
+/* Label box, darken color on hover, fitted */
+#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {
+  color: var(--sklearn-color-text);
+  background-color: var(--sklearn-color-fitted-level-2);
+}
+
+/* Estimator label */
+
+#sk-container-id-2 div.sk-label label {
+  font-family: monospace;
+  font-weight: bold;
+  display: inline-block;
+  line-height: 1.2em;
+}
+
+#sk-container-id-2 div.sk-label-container {
+  text-align: center;
+}
+
+/* Estimator-specific */
+#sk-container-id-2 div.sk-estimator {
+  font-family: monospace;
+  border: 1px dotted var(--sklearn-color-border-box);
+  border-radius: 0.25em;
+  box-sizing: border-box;
+  margin-bottom: 0.5em;
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-0);
+}
+
+#sk-container-id-2 div.sk-estimator.fitted {
+  /* fitted */
+  background-color: var(--sklearn-color-fitted-level-0);
+}
+
+/* on hover */
+#sk-container-id-2 div.sk-estimator:hover {
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-2);
+}
+
+#sk-container-id-2 div.sk-estimator.fitted:hover {
+  /* fitted */
+  background-color: var(--sklearn-color-fitted-level-2);
+}
+
+/* Specification for estimator info (e.g. "i" and "?") */
+
+/* Common style for "i" and "?" */
+
+.sk-estimator-doc-link,
+a:link.sk-estimator-doc-link,
+a:visited.sk-estimator-doc-link {
+  float: right;
+  font-size: smaller;
+  line-height: 1em;
+  font-family: monospace;
+  background-color: var(--sklearn-color-background);
+  border-radius: 1em;
+  height: 1em;
+  width: 1em;
+  text-decoration: none !important;
+  margin-left: 1ex;
+  /* unfitted */
+  border: var(--sklearn-color-unfitted-level-1) 1pt solid;
+  color: var(--sklearn-color-unfitted-level-1);
+}
+
+.sk-estimator-doc-link.fitted,
+a:link.sk-estimator-doc-link.fitted,
+a:visited.sk-estimator-doc-link.fitted {
+  /* fitted */
+  border: var(--sklearn-color-fitted-level-1) 1pt solid;
+  color: var(--sklearn-color-fitted-level-1);
+}
+
+/* On hover */
+div.sk-estimator:hover .sk-estimator-doc-link:hover,
+.sk-estimator-doc-link:hover,
+div.sk-label-container:hover .sk-estimator-doc-link:hover,
+.sk-estimator-doc-link:hover {
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-3);
+  color: var(--sklearn-color-background);
+  text-decoration: none;
+}
+
+div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,
+.sk-estimator-doc-link.fitted:hover,
+div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,
+.sk-estimator-doc-link.fitted:hover {
+  /* fitted */
+  background-color: var(--sklearn-color-fitted-level-3);
+  color: var(--sklearn-color-background);
+  text-decoration: none;
+}
+
+/* Span, style for the box shown on hovering the info icon */
+.sk-estimator-doc-link span {
+  display: none;
+  z-index: 9999;
+  position: relative;
+  font-weight: normal;
+  right: .2ex;
+  padding: .5ex;
+  margin: .5ex;
+  width: min-content;
+  min-width: 20ex;
+  max-width: 50ex;
+  color: var(--sklearn-color-text);
+  box-shadow: 2pt 2pt 4pt #999;
+  /* unfitted */
+  background: var(--sklearn-color-unfitted-level-0);
+  border: .5pt solid var(--sklearn-color-unfitted-level-3);
+}
+
+.sk-estimator-doc-link.fitted span {
+  /* fitted */
+  background: var(--sklearn-color-fitted-level-0);
+  border: var(--sklearn-color-fitted-level-3);
+}
+
+.sk-estimator-doc-link:hover span {
+  display: block;
+}
+
+/* "?"-specific style due to the `<a>` HTML tag */
+
+#sk-container-id-2 a.estimator_doc_link {
+  float: right;
+  font-size: 1rem;
+  line-height: 1em;
+  font-family: monospace;
+  background-color: var(--sklearn-color-background);
+  border-radius: 1rem;
+  height: 1rem;
+  width: 1rem;
+  text-decoration: none;
+  /* unfitted */
+  color: var(--sklearn-color-unfitted-level-1);
+  border: var(--sklearn-color-unfitted-level-1) 1pt solid;
+}
+
+#sk-container-id-2 a.estimator_doc_link.fitted {
+  /* fitted */
+  border: var(--sklearn-color-fitted-level-1) 1pt solid;
+  color: var(--sklearn-color-fitted-level-1);
+}
+
+/* On hover */
+#sk-container-id-2 a.estimator_doc_link:hover {
+  /* unfitted */
+  background-color: var(--sklearn-color-unfitted-level-3);
+  color: var(--sklearn-color-background);
+  text-decoration: none;
+}
+
+#sk-container-id-2 a.estimator_doc_link.fitted:hover {
+  /* fitted */
+  background-color: var(--sklearn-color-fitted-level-3);
+}
+</style><div id="sk-container-id-2" class="sk-top-container"><div class="sk-text-repr-fallback"><pre>RandomForestRegressor(max_depth=34)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden><div class="sk-item"><div class="sk-estimator fitted sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-2" type="checkbox" checked><label for="sk-estimator-id-2" class="sk-toggleable__label fitted sk-toggleable__label-arrow fitted">&nbsp;&nbsp;RandomForestRegressor<a class="sk-estimator-doc-link fitted" rel="noreferrer" target="_blank" href="https://scikit-learn.org/1.5/modules/generated/sklearn.ensemble.RandomForestRegressor.html">?<span>Documentation for RandomForestRegressor</span></a><span class="sk-estimator-doc-link fitted">i<span>Fitted</span></span></label><div class="sk-toggleable__content fitted"><pre>RandomForestRegressor(max_depth=34)</pre></div> </div></div></div></div>
+  </body>
+</html>
+    

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mlartifacts/674375719018272828/f431bc7dfc364411bfea5e73327458d1/artifacts/model/MLmodel

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+artifact_path: model
+flavors:
+  python_function:
+    data: model.xgb
+    env:
+      conda: conda.yaml
+      virtualenv: python_env.yaml
+    loader_module: mlflow.xgboost
+    python_version: 3.11.0
+  xgboost:
+    code: null
+    data: model.xgb
+    model_class: xgboost.sklearn.XGBRegressor
+    model_format: xgb
+    xgb_version: 2.1.1
+mlflow_version: 2.16.2
+model_size_bytes: 12354728
+model_uuid: e6dbc474179049ceaf181dcb2d2477ba
+run_id: f431bc7dfc364411bfea5e73327458d1
+signature:
+  inputs: '[{"type": "tensor", "tensor-spec": {"dtype": "float64", "shape": [-1, 33]}}]'
+  outputs: '[{"type": "tensor", "tensor-spec": {"dtype": "float32", "shape": [-1,
+    6]}}]'
+  params: null
+utc_time_created: '2024-09-30 13:22:22.959048'

mlartifacts/674375719018272828/f431bc7dfc364411bfea5e73327458d1/artifacts/model/conda.yaml

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+channels:
+- conda-forge
+dependencies:
+- python=3.11.0
+- pip<=24.2
+- pip:
+  - mlflow==2.16.2
+  - numpy==1.26.2
+  - pandas==2.2.2
+  - psutil==5.9.4
+  - scikit-learn==1.5.2
+  - scipy==1.11.4
+  - typing==3.7.4.3
+  - xgboost==2.1.1
+name: mlflow-env

mlartifacts/674375719018272828/f431bc7dfc364411bfea5e73327458d1/artifacts/model/model.xgb

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+version https://git-lfs.github.com/spec/v1
+oid sha256:c823873e6e051da216bde5618c3db8390d1cdc8e1edd143c59272d69548fc05f
+size 12354728

mlartifacts/674375719018272828/f431bc7dfc364411bfea5e73327458d1/artifacts/model/python_env.yaml

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+python: 3.11.0
+build_dependencies:
+- pip==24.2
+- setuptools==65.5.0
+- wheel==0.41.2
+dependencies:
+- -r requirements.txt

mlartifacts/674375719018272828/f431bc7dfc364411bfea5e73327458d1/artifacts/model/requirements.txt

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+mlflow==2.16.2
+numpy==1.26.2
+pandas==2.2.2
+psutil==5.9.4
+scikit-learn==1.5.2
+scipy==1.11.4
+typing==3.7.4.3
+xgboost==2.1.1