Baseline Model trained on titanic_traink4m62li8 to apply classification on survived
Metrics of the best model:
accuracy 0.975294
average_precision 0.983664
roc_auc 0.987422
recall_macro 0.971786
f1_macro 0.973370
Name: MultinomialNB(), dtype: float64
See model plot below:
Pipeline(steps=[('easypreprocessor',EasyPreprocessor(types= continuous dirty_float ... free_string useless
passenger_id True False ... False False
pclass False False ... False False
name False False ... True False
sex False False ... False False
age True False ... False False
sibsp False False ... False False
parch False False ... False False
ticket False False ... True False
fare True False ... False False
cabin False False ... True False
embarked False False ... False False
boat False False ... False False
body True False ... False False
home.dest False False ... True False[14 rows x 7 columns])),('pipeline',Pipeline(steps=[('minmaxscaler', MinMaxScaler()),('multinomialnb', MultinomialNB())]))])
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
Pipeline(steps=[('easypreprocessor',EasyPreprocessor(types= continuous dirty_float ... free_string useless
passenger_id True False ... False False
pclass False False ... False False
name False False ... True False
sex False False ... False False
age True False ... False False
sibsp False False ... False False
parch False False ... False False
ticket False False ... True False
fare True False ... False False
cabin False False ... True False
embarked False False ... False False
boat False False ... False False
body True False ... False False
home.dest False False ... True False[14 rows x 7 columns])),('pipeline',Pipeline(steps=[('minmaxscaler', MinMaxScaler()),('multinomialnb', MultinomialNB())]))])EasyPreprocessor(types= continuous dirty_float ... free_string useless passenger_id True False ... False False pclass False False ... False False name False False ... True False sex False False ... False False age True False ... False False sibsp False False ... False False parch False False ... False False ticket False False ... True False fare True False ... False False cabin False False ... True False embarked False False ... False False boat False False ... False False body True False ... False False home.dest False False ... True False[14 rows x 7 columns])
Pipeline(steps=[('minmaxscaler', MinMaxScaler()),('multinomialnb', MultinomialNB())])MinMaxScaler()
MultinomialNB()
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