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.

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

Downloads last month
0
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.