Baseline Model trained on arinfo_sample_dataset_finaltffwjv58 to apply classification on model
Metrics of the best model:
accuracy 0.930688
recall_macro 0.655991
precision_macro 0.640972
f1_macro 0.638021
Name: DecisionTreeClassifier(class_weight='balanced', max_depth=2249), dtype: float64
See model plot below:
Pipeline(steps=[('easypreprocessor',EasyPreprocessor(types=             continuous  dirty_float  low_card_int  ...   date  free_string  useless
rto               False        False         False  ...  False         True    False
ownerNum          False        False         False  ...  False        False    False
cc                False        False         False  ...  False        False    False
insurance         False        False         False  ...  False        False    False
weight             True        False         False  ...  False        False    False
financer          False        False         False  ...  False         True    False
fu...
class             False        False         False  ...  False        False    False
state             False        False         False  ...  False        False    False
year              False        False         False  ...  False        False    False
categoryId        False        False         False  ...  False        False    False
onroadPrice        True        False         False  ...  False        False    False
price_FAIR         True        False         False  ...  False        False    False[13 rows x 7 columns])),('decisiontreeclassifier',DecisionTreeClassifier(class_weight='balanced',max_depth=2249))])
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  low_card_int  ...   date  free_string  useless
rto               False        False         False  ...  False         True    False
ownerNum          False        False         False  ...  False        False    False
cc                False        False         False  ...  False        False    False
insurance         False        False         False  ...  False        False    False
weight             True        False         False  ...  False        False    False
financer          False        False         False  ...  False         True    False
fu...
class             False        False         False  ...  False        False    False
state             False        False         False  ...  False        False    False
year              False        False         False  ...  False        False    False
categoryId        False        False         False  ...  False        False    False
onroadPrice        True        False         False  ...  False        False    False
price_FAIR         True        False         False  ...  False        False    False[13 rows x 7 columns])),('decisiontreeclassifier',DecisionTreeClassifier(class_weight='balanced',max_depth=2249))])EasyPreprocessor(types= continuous dirty_float low_card_int ... date free_string useless rto False False False ... False True False ownerNum False False False ... False False False cc False False False ... False False False insurance False False False ... False False False weight True False False ... False False False financer False False False ... False True False fuelType False False False ... False False False class False False False ... False False False state False False False ... False False False year False False False ... False False False categoryId False False False ... False False False onroadPrice True False False ... False False False price_FAIR True False False ... False False False[13 rows x 7 columns])
DecisionTreeClassifier(class_weight='balanced', max_depth=2249)
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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