README.md

metadata

license: apache-2.0
library_name: sklearn
tags:
  - tabular-classification
  - baseline-trainer

Baseline Model trained on accentcombinedlenous8ktq9 to apply classification on accent

Metrics of the best model:

accuracy 0.947980

recall_macro 0.749094

precision_macro 0.622545

f1_macro 0.656714

Name: LogisticRegression(C=1, class_weight='balanced', max_iter=1000), dtype: float64

See model plot below:

Pipeline(steps=[('easypreprocessor',EasyPreprocessor(types=         continuous  dirty_float  low_card_int  ...   date  free_string  useless
word          False        False         False  ...  False         True    False
kana          False        False         False  ...  False         True    False
kind          False        False         False  ...  False        False    False
morae         False        False         False  ...  False        False    False
pos           False        False         False  ...  False        False    False
etym          False        False         False  ...  False        False    False
jilen         False        False         False  ...  False        False    False
kanalen       False        False         False  ...  False        False    False[8 rows x 7 columns])),('logisticregression',LogisticRegression(C=1, class_weight='balanced',max_iter=1000))])

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