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))])
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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))])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(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