pushing files from first example to the repo
Browse files- README.md +239 -0
- config.json +183 -0
- confusion_matrix.png +0 -0
- rf_model.pkl +3 -0
README.md
ADDED
|
@@ -0,0 +1,239 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: mit
|
| 3 |
+
library_name: sklearn
|
| 4 |
+
tags:
|
| 5 |
+
- sklearn
|
| 6 |
+
- skops
|
| 7 |
+
- tabular-classification
|
| 8 |
+
widget:
|
| 9 |
+
structuredData:
|
| 10 |
+
x0:
|
| 11 |
+
- 0.6666666666666667
|
| 12 |
+
- 1.0
|
| 13 |
+
- 1.0
|
| 14 |
+
x1:
|
| 15 |
+
- 0.0
|
| 16 |
+
- 0.0
|
| 17 |
+
- 0.0
|
| 18 |
+
x10:
|
| 19 |
+
- 0.0
|
| 20 |
+
- 0.0
|
| 21 |
+
- 0.0
|
| 22 |
+
x11:
|
| 23 |
+
- 0.0
|
| 24 |
+
- 1.0
|
| 25 |
+
- 0.0
|
| 26 |
+
x12:
|
| 27 |
+
- 1.0
|
| 28 |
+
- 0.0
|
| 29 |
+
- 1.0
|
| 30 |
+
x13:
|
| 31 |
+
- 0.0
|
| 32 |
+
- 0.0
|
| 33 |
+
- 0.0
|
| 34 |
+
x14:
|
| 35 |
+
- 0.0
|
| 36 |
+
- 0.0
|
| 37 |
+
- 0.0
|
| 38 |
+
x15:
|
| 39 |
+
- 1.0
|
| 40 |
+
- 0.0
|
| 41 |
+
- 0.0
|
| 42 |
+
x16:
|
| 43 |
+
- 0.0
|
| 44 |
+
- 0.0
|
| 45 |
+
- 0.0
|
| 46 |
+
x17:
|
| 47 |
+
- 0.0
|
| 48 |
+
- 0.0
|
| 49 |
+
- 1.0
|
| 50 |
+
x18:
|
| 51 |
+
- 0.0
|
| 52 |
+
- 0.0
|
| 53 |
+
- 0.0
|
| 54 |
+
x19:
|
| 55 |
+
- 0.0
|
| 56 |
+
- 1.0
|
| 57 |
+
- 0.0
|
| 58 |
+
x2:
|
| 59 |
+
- 1.0
|
| 60 |
+
- 1.0
|
| 61 |
+
- 1.0
|
| 62 |
+
x20:
|
| 63 |
+
- 1.0
|
| 64 |
+
- 0.0
|
| 65 |
+
- 0.0
|
| 66 |
+
x21:
|
| 67 |
+
- 0.0
|
| 68 |
+
- 1.0
|
| 69 |
+
- 1.0
|
| 70 |
+
x22:
|
| 71 |
+
- 0.0
|
| 72 |
+
- 0.0
|
| 73 |
+
- 0.0
|
| 74 |
+
x23:
|
| 75 |
+
- 1.0
|
| 76 |
+
- 0.0
|
| 77 |
+
- 1.0
|
| 78 |
+
x24:
|
| 79 |
+
- 0.0
|
| 80 |
+
- 0.0
|
| 81 |
+
- 0.0
|
| 82 |
+
x25:
|
| 83 |
+
- 0.0
|
| 84 |
+
- 0.0
|
| 85 |
+
- 0.0
|
| 86 |
+
x26:
|
| 87 |
+
- 0.0
|
| 88 |
+
- 0.0
|
| 89 |
+
- 0.0
|
| 90 |
+
x27:
|
| 91 |
+
- 0.0
|
| 92 |
+
- 1.0
|
| 93 |
+
- 0.0
|
| 94 |
+
x3:
|
| 95 |
+
- 0.0
|
| 96 |
+
- 1.0
|
| 97 |
+
- 0.0
|
| 98 |
+
x4:
|
| 99 |
+
- 0.0
|
| 100 |
+
- 0.0
|
| 101 |
+
- 1.0
|
| 102 |
+
x5:
|
| 103 |
+
- 1.0
|
| 104 |
+
- 0.0
|
| 105 |
+
- 0.0
|
| 106 |
+
x6:
|
| 107 |
+
- 0.0
|
| 108 |
+
- 0.0
|
| 109 |
+
- 0.0
|
| 110 |
+
x7:
|
| 111 |
+
- 0.24999999999999997
|
| 112 |
+
- 0.14285714285714285
|
| 113 |
+
- 0.3571428571428571
|
| 114 |
+
x8:
|
| 115 |
+
- 0.4772654358070523
|
| 116 |
+
- 0.47033921746222385
|
| 117 |
+
- 0.32320252247170167
|
| 118 |
+
x9:
|
| 119 |
+
- 0.0
|
| 120 |
+
- 0.0
|
| 121 |
+
- 0.0
|
| 122 |
+
---
|
| 123 |
+
|
| 124 |
+
# Model description
|
| 125 |
+
|
| 126 |
+
This is a Random Forest model trained on entire set of features from data provided by Reunion.
|
| 127 |
+
|
| 128 |
+
## Intended uses & limitations
|
| 129 |
+
|
| 130 |
+
This model is not fine-tuned for production.
|
| 131 |
+
|
| 132 |
+
## Training Procedure
|
| 133 |
+
|
| 134 |
+
### Hyperparameters
|
| 135 |
+
|
| 136 |
+
The model is trained with below hyperparameters.
|
| 137 |
+
|
| 138 |
+
<details>
|
| 139 |
+
<summary> Click to expand </summary>
|
| 140 |
+
|
| 141 |
+
| Hyperparameter | Value |
|
| 142 |
+
|-------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|
| 143 |
+
| cv | 3 |
|
| 144 |
+
| error_score | nan |
|
| 145 |
+
| estimator__bootstrap | True |
|
| 146 |
+
| estimator__ccp_alpha | 0.0 |
|
| 147 |
+
| estimator__class_weight | balanced |
|
| 148 |
+
| estimator__criterion | gini |
|
| 149 |
+
| estimator__max_depth | |
|
| 150 |
+
| estimator__max_features | auto |
|
| 151 |
+
| estimator__max_leaf_nodes | |
|
| 152 |
+
| estimator__max_samples | |
|
| 153 |
+
| estimator__min_impurity_decrease | 0.0 |
|
| 154 |
+
| estimator__min_impurity_split | |
|
| 155 |
+
| estimator__min_samples_leaf | 1 |
|
| 156 |
+
| estimator__min_samples_split | 2 |
|
| 157 |
+
| estimator__min_weight_fraction_leaf | 0.0 |
|
| 158 |
+
| estimator__n_estimators | 100 |
|
| 159 |
+
| estimator__n_jobs | -1 |
|
| 160 |
+
| estimator__oob_score | False |
|
| 161 |
+
| estimator__random_state | 42 |
|
| 162 |
+
| estimator__verbose | 1 |
|
| 163 |
+
| estimator__warm_start | False |
|
| 164 |
+
| estimator | RandomForestClassifier(class_weight='balanced', n_jobs=-1, random_state=42,
|
| 165 |
+
verbose=1) |
|
| 166 |
+
| n_iter | 100 |
|
| 167 |
+
| n_jobs | -1 |
|
| 168 |
+
| param_distributions | {'n_estimators': [200, 400, 600, 800, 1000, 1200, 1400, 1600, 1800, 2000], 'max_features': ['auto', 'sqrt'], 'max_depth': [10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, None], 'min_samples_split': [2, 5, 10], 'min_samples_leaf': [1, 2, 4], 'bootstrap': [True, False]} |
|
| 169 |
+
| pre_dispatch | 2*n_jobs |
|
| 170 |
+
| random_state | 42 |
|
| 171 |
+
| refit | True |
|
| 172 |
+
| return_train_score | False |
|
| 173 |
+
| scoring | |
|
| 174 |
+
| verbose | 2 |
|
| 175 |
+
|
| 176 |
+
</details>
|
| 177 |
+
|
| 178 |
+
### Model Plot
|
| 179 |
+
|
| 180 |
+
The model plot is below.
|
| 181 |
+
|
| 182 |
+
<style>#sk-612ecc16-5410-4287-9cca-3bb6bb70aa61 {color: black;background-color: white;}#sk-612ecc16-5410-4287-9cca-3bb6bb70aa61 pre{padding: 0;}#sk-612ecc16-5410-4287-9cca-3bb6bb70aa61 div.sk-toggleable {background-color: white;}#sk-612ecc16-5410-4287-9cca-3bb6bb70aa61 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.2em 0.3em;box-sizing: border-box;text-align: center;}#sk-612ecc16-5410-4287-9cca-3bb6bb70aa61 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-612ecc16-5410-4287-9cca-3bb6bb70aa61 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-612ecc16-5410-4287-9cca-3bb6bb70aa61 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-612ecc16-5410-4287-9cca-3bb6bb70aa61 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-612ecc16-5410-4287-9cca-3bb6bb70aa61 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-612ecc16-5410-4287-9cca-3bb6bb70aa61 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-612ecc16-5410-4287-9cca-3bb6bb70aa61 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;margin: 0.25em 0.25em;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;}#sk-612ecc16-5410-4287-9cca-3bb6bb70aa61 div.sk-estimator:hover {background-color: #d4ebff;}#sk-612ecc16-5410-4287-9cca-3bb6bb70aa61 div.sk-parallel-item::after {content: "";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-612ecc16-5410-4287-9cca-3bb6bb70aa61 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-612ecc16-5410-4287-9cca-3bb6bb70aa61 div.sk-serial::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 2em;bottom: 0;left: 50%;}#sk-612ecc16-5410-4287-9cca-3bb6bb70aa61 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;}#sk-612ecc16-5410-4287-9cca-3bb6bb70aa61 div.sk-item {z-index: 1;}#sk-612ecc16-5410-4287-9cca-3bb6bb70aa61 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;}#sk-612ecc16-5410-4287-9cca-3bb6bb70aa61 div.sk-parallel-item {display: flex;flex-direction: column;position: relative;background-color: white;}#sk-612ecc16-5410-4287-9cca-3bb6bb70aa61 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-612ecc16-5410-4287-9cca-3bb6bb70aa61 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-612ecc16-5410-4287-9cca-3bb6bb70aa61 div.sk-parallel-item:only-child::after {width: 0;}#sk-612ecc16-5410-4287-9cca-3bb6bb70aa61 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0.2em;box-sizing: border-box;padding-bottom: 0.1em;background-color: white;position: relative;}#sk-612ecc16-5410-4287-9cca-3bb6bb70aa61 div.sk-label label {font-family: monospace;font-weight: bold;background-color: white;display: inline-block;line-height: 1.2em;}#sk-612ecc16-5410-4287-9cca-3bb6bb70aa61 div.sk-label-container {position: relative;z-index: 2;text-align: center;}#sk-612ecc16-5410-4287-9cca-3bb6bb70aa61 div.sk-container {display: inline-block;position: relative;}</style><div id="sk-612ecc16-5410-4287-9cca-3bb6bb70aa61" class"sk-top-container"><div class="sk-container"><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="e81b924e-93ea-42c0-84fd-af8e0ec97962" type="checkbox" ><label class="sk-toggleable__label" for="e81b924e-93ea-42c0-84fd-af8e0ec97962">RandomizedSearchCV</label><div class="sk-toggleable__content"><pre>RandomizedSearchCV(cv=3,estimator=RandomForestClassifier(class_weight='balanced',n_jobs=-1, random_state=42,verbose=1),n_iter=100, n_jobs=-1,param_distributions={'bootstrap': [True, False],'max_depth': [10, 20, 30, 40, 50, 60,70, 80, 90, 100, 110,None],'max_features': ['auto', 'sqrt'],'min_samples_leaf': [1, 2, 4],'min_samples_split': [2, 5, 10],'n_estimators': [200, 400, 600, 800,1000, 1200, 1400, 1600,1800, 2000]},random_state=42, verbose=2)</pre></div></div></div><div class="sk-parallel"><div class="sk-parallel-item"><div class="sk-item"><div class="sk-serial"><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="4a4e6c45-5264-4a41-8fbe-d7cb73b658bb" type="checkbox" ><label class="sk-toggleable__label" for="4a4e6c45-5264-4a41-8fbe-d7cb73b658bb">RandomForestClassifier</label><div class="sk-toggleable__content"><pre>RandomForestClassifier(class_weight='balanced', n_jobs=-1, random_state=42,verbose=1)</pre></div></div></div></div></div></div></div></div></div></div>
|
| 183 |
+
|
| 184 |
+
##Â Evaluation Results
|
| 185 |
+
|
| 186 |
+
You can find the details about evaluation process and the evaluation results.
|
| 187 |
+
|
| 188 |
+
|
| 189 |
+
|
| 190 |
+
| Metric | Value |
|
| 191 |
+
|----------|---------|
|
| 192 |
+
| accuracy | 0.705 |
|
| 193 |
+
| recall | 0.05 |
|
| 194 |
+
|
| 195 |
+
# How to Get Started with the Model
|
| 196 |
+
|
| 197 |
+
Use the code below to get started with the model.
|
| 198 |
+
|
| 199 |
+
<details>
|
| 200 |
+
<summary> Click to expand </summary>
|
| 201 |
+
|
| 202 |
+
```python
|
| 203 |
+
import pickle
|
| 204 |
+
with open(dtc_pkl_filename, 'rb') as file:
|
| 205 |
+
clf = pickle.load(file)
|
| 206 |
+
```
|
| 207 |
+
|
| 208 |
+
</details>
|
| 209 |
+
|
| 210 |
+
|
| 211 |
+
|
| 212 |
+
|
| 213 |
+
# Model Card Authors
|
| 214 |
+
|
| 215 |
+
This model card is written by following authors:
|
| 216 |
+
|
| 217 |
+
kushkul
|
| 218 |
+
|
| 219 |
+
# Model Card Contact
|
| 220 |
+
|
| 221 |
+
You can contact the model card authors through following channels:
|
| 222 |
+
[More Information Needed]
|
| 223 |
+
|
| 224 |
+
# Citation
|
| 225 |
+
|
| 226 |
+
Below you can find information related to citation.
|
| 227 |
+
|
| 228 |
+
**BibTeX:**
|
| 229 |
+
```
|
| 230 |
+
bibtex
|
| 231 |
+
@inproceedings{...,year={2022}}
|
| 232 |
+
```
|
| 233 |
+
|
| 234 |
+
|
| 235 |
+
# Additional Content
|
| 236 |
+
|
| 237 |
+
## confusion_matrix
|
| 238 |
+
|
| 239 |
+
|
config.json
ADDED
|
@@ -0,0 +1,183 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"sklearn": {
|
| 3 |
+
"columns": [
|
| 4 |
+
"x0",
|
| 5 |
+
"x1",
|
| 6 |
+
"x2",
|
| 7 |
+
"x3",
|
| 8 |
+
"x4",
|
| 9 |
+
"x5",
|
| 10 |
+
"x6",
|
| 11 |
+
"x7",
|
| 12 |
+
"x8",
|
| 13 |
+
"x9",
|
| 14 |
+
"x10",
|
| 15 |
+
"x11",
|
| 16 |
+
"x12",
|
| 17 |
+
"x13",
|
| 18 |
+
"x14",
|
| 19 |
+
"x15",
|
| 20 |
+
"x16",
|
| 21 |
+
"x17",
|
| 22 |
+
"x18",
|
| 23 |
+
"x19",
|
| 24 |
+
"x20",
|
| 25 |
+
"x21",
|
| 26 |
+
"x22",
|
| 27 |
+
"x23",
|
| 28 |
+
"x24",
|
| 29 |
+
"x25",
|
| 30 |
+
"x26",
|
| 31 |
+
"x27"
|
| 32 |
+
],
|
| 33 |
+
"environment": [
|
| 34 |
+
"scikit-learn=0.24.2"
|
| 35 |
+
],
|
| 36 |
+
"example_input": {
|
| 37 |
+
"x0": [
|
| 38 |
+
0.6666666666666667,
|
| 39 |
+
1.0,
|
| 40 |
+
1.0
|
| 41 |
+
],
|
| 42 |
+
"x1": [
|
| 43 |
+
0.0,
|
| 44 |
+
0.0,
|
| 45 |
+
0.0
|
| 46 |
+
],
|
| 47 |
+
"x10": [
|
| 48 |
+
0.0,
|
| 49 |
+
0.0,
|
| 50 |
+
0.0
|
| 51 |
+
],
|
| 52 |
+
"x11": [
|
| 53 |
+
0.0,
|
| 54 |
+
1.0,
|
| 55 |
+
0.0
|
| 56 |
+
],
|
| 57 |
+
"x12": [
|
| 58 |
+
1.0,
|
| 59 |
+
0.0,
|
| 60 |
+
1.0
|
| 61 |
+
],
|
| 62 |
+
"x13": [
|
| 63 |
+
0.0,
|
| 64 |
+
0.0,
|
| 65 |
+
0.0
|
| 66 |
+
],
|
| 67 |
+
"x14": [
|
| 68 |
+
0.0,
|
| 69 |
+
0.0,
|
| 70 |
+
0.0
|
| 71 |
+
],
|
| 72 |
+
"x15": [
|
| 73 |
+
1.0,
|
| 74 |
+
0.0,
|
| 75 |
+
0.0
|
| 76 |
+
],
|
| 77 |
+
"x16": [
|
| 78 |
+
0.0,
|
| 79 |
+
0.0,
|
| 80 |
+
0.0
|
| 81 |
+
],
|
| 82 |
+
"x17": [
|
| 83 |
+
0.0,
|
| 84 |
+
0.0,
|
| 85 |
+
1.0
|
| 86 |
+
],
|
| 87 |
+
"x18": [
|
| 88 |
+
0.0,
|
| 89 |
+
0.0,
|
| 90 |
+
0.0
|
| 91 |
+
],
|
| 92 |
+
"x19": [
|
| 93 |
+
0.0,
|
| 94 |
+
1.0,
|
| 95 |
+
0.0
|
| 96 |
+
],
|
| 97 |
+
"x2": [
|
| 98 |
+
1.0,
|
| 99 |
+
1.0,
|
| 100 |
+
1.0
|
| 101 |
+
],
|
| 102 |
+
"x20": [
|
| 103 |
+
1.0,
|
| 104 |
+
0.0,
|
| 105 |
+
0.0
|
| 106 |
+
],
|
| 107 |
+
"x21": [
|
| 108 |
+
0.0,
|
| 109 |
+
1.0,
|
| 110 |
+
1.0
|
| 111 |
+
],
|
| 112 |
+
"x22": [
|
| 113 |
+
0.0,
|
| 114 |
+
0.0,
|
| 115 |
+
0.0
|
| 116 |
+
],
|
| 117 |
+
"x23": [
|
| 118 |
+
1.0,
|
| 119 |
+
0.0,
|
| 120 |
+
1.0
|
| 121 |
+
],
|
| 122 |
+
"x24": [
|
| 123 |
+
0.0,
|
| 124 |
+
0.0,
|
| 125 |
+
0.0
|
| 126 |
+
],
|
| 127 |
+
"x25": [
|
| 128 |
+
0.0,
|
| 129 |
+
0.0,
|
| 130 |
+
0.0
|
| 131 |
+
],
|
| 132 |
+
"x26": [
|
| 133 |
+
0.0,
|
| 134 |
+
0.0,
|
| 135 |
+
0.0
|
| 136 |
+
],
|
| 137 |
+
"x27": [
|
| 138 |
+
0.0,
|
| 139 |
+
1.0,
|
| 140 |
+
0.0
|
| 141 |
+
],
|
| 142 |
+
"x3": [
|
| 143 |
+
0.0,
|
| 144 |
+
1.0,
|
| 145 |
+
0.0
|
| 146 |
+
],
|
| 147 |
+
"x4": [
|
| 148 |
+
0.0,
|
| 149 |
+
0.0,
|
| 150 |
+
1.0
|
| 151 |
+
],
|
| 152 |
+
"x5": [
|
| 153 |
+
1.0,
|
| 154 |
+
0.0,
|
| 155 |
+
0.0
|
| 156 |
+
],
|
| 157 |
+
"x6": [
|
| 158 |
+
0.0,
|
| 159 |
+
0.0,
|
| 160 |
+
0.0
|
| 161 |
+
],
|
| 162 |
+
"x7": [
|
| 163 |
+
0.24999999999999997,
|
| 164 |
+
0.14285714285714285,
|
| 165 |
+
0.3571428571428571
|
| 166 |
+
],
|
| 167 |
+
"x8": [
|
| 168 |
+
0.4772654358070523,
|
| 169 |
+
0.47033921746222385,
|
| 170 |
+
0.32320252247170167
|
| 171 |
+
],
|
| 172 |
+
"x9": [
|
| 173 |
+
0.0,
|
| 174 |
+
0.0,
|
| 175 |
+
0.0
|
| 176 |
+
]
|
| 177 |
+
},
|
| 178 |
+
"model": {
|
| 179 |
+
"file": "rf_model.pkl"
|
| 180 |
+
},
|
| 181 |
+
"task": "tabular-classification"
|
| 182 |
+
}
|
| 183 |
+
}
|
confusion_matrix.png
ADDED
|
rf_model.pkl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0a11231c1d03af07d36f7877a6391c27d6b95421caaeb4df19a2d56118fc82a9
|
| 3 |
+
size 5588710
|