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Baseline Model trained on titanicht_mp88q to apply classification on Survived

Metrics of the best model:

accuracy 0.803597

average_precision 0.801332

roc_auc 0.848079

recall_macro 0.795883

f1_macro 0.793746

Name: DecisionTreeClassifier(class_weight='balanced', max_depth=5), dtype: float64

See model plot below:

Pipeline(steps=[('easypreprocessor',EasyPreprocessor(types=          continuous  dirty_float  low_card_int  ...   date  free_string  useless

Pclass False False False ... False False False Name False False False ... False True False Sex False False False ... False False False Age True False False ... False False False SibSp False False False ... False False False Parch False False False ... False False False Ticket False False False ... False True False Fare True False False ... False False False Cabin False False False ... False True False Embarked False False False ... False False False[10 rows x 7 columns])),('decisiontreeclassifier',DecisionTreeClassifier(class_weight='balanced', max_depth=5))])

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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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