Baseline Model trained on irisg444_4c0 to apply classification on Species
Metrics of the best model:
accuracy 0.953333
recall_macro 0.953333
precision_macro 0.956229
f1_macro 0.953216
Name: LogisticRegression(class_weight='balanced', max_iter=1000), dtype: float64
See model plot below:
Pipeline(steps=[('easypreprocessor',EasyPreprocessor(types=               continuous  dirty_float  ...  free_string  useless
SepalLengthCm        True        False  ...        False    False
SepalWidthCm         True        False  ...        False    False
PetalLengthCm        True        False  ...        False    False
PetalWidthCm         True        False  ...        False    False[4 rows x 7 columns])),('logisticregression',LogisticRegression(C=1, class_weight='balanced',max_iter=1000))])
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Pipeline(steps=[('easypreprocessor',EasyPreprocessor(types=               continuous  dirty_float  ...  free_string  useless
SepalLengthCm        True        False  ...        False    False
SepalWidthCm         True        False  ...        False    False
PetalLengthCm        True        False  ...        False    False
PetalWidthCm         True        False  ...        False    False[4 rows x 7 columns])),('logisticregression',LogisticRegression(C=1, class_weight='balanced',max_iter=1000))])EasyPreprocessor(types= continuous dirty_float ... free_string useless SepalLengthCm True False ... False False SepalWidthCm True False ... False False PetalLengthCm True False ... False False PetalWidthCm True False ... False False[4 rows x 7 columns])
LogisticRegression(C=1, class_weight='balanced', max_iter=1000)
Disclaimer: This model is trained with dabl library as a baseline, for better results, use AutoTrain.
Logs of training including the models tried in the process can be found in logs.txt
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