How to use from the
Use from the
Scikit-learn library
# Gated model: Login with a HF token with gated access permission
hf auth login
from huggingface_hub import hf_hub_download
import joblib
model = joblib.load(
	hf_hub_download("kkiskk/alidatelcyrtea0-auditStatus-classification", "sklearn_model.joblib")
)
# only load pickle files from sources you trust
# read more about it here https://skops.readthedocs.io/en/stable/persistence.html

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Baseline Model trained on alidatelcyrtea0 to apply classification on auditStatus

Metrics of the best model:

accuracy 1.0

average_precision 1.0

roc_auc 1.0

recall_macro 1.0

f1_macro 1.0

Name: DecisionTreeClassifier(class_weight='balanced', max_depth=5), dtype: float64

See model plot below:

Pipeline(steps=[('easypreprocessor',EasyPreprocessor(types=             continuous  dirty_float  low_card_int  ...   date  free_string  useless

DrawMoney False False False ... False False False DrawCount False False False ... False False False LastDrawMin True False False ... False False False SignUpMin True False False ... False False False Balance True False False ... False False False TodayMoney False False False ... False False False[6 rows x 7 columns])),('decisiontreeclassifier',DecisionTreeClassifier(class_weight='balanced', max_depth=5))])

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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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