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Comments (3)

aplonska avatar aplonska commented on May 29, 2024 1

Is it helpful?

from docs.

aplonska avatar aplonska commented on May 29, 2024
Available modes
explain perform compete
Uses models:
Baseline +
Linear + + +
Decision Tree + +
Random Forest + + +
XGBoost + + +
Neural Network + + +
Ensemble + + +
Light GBM +
CatBoost + +
Extra Trees +
Nearest Neighbors +
Stacking +
Validation:
Uses 75%/25% train/test split Uses a 5-fold CV (Cross-Validation) with shuffle and stratification Uses 10-fold CV (Cross-Validation) with shuffle and stratification
Explanations:
explain_level=2 explain_level=1 explain_level=0
Steps:
Learning curves + + +
Importance plots + +
SHAP plots +
Steps
simple_algorithms + + +
default_algorithms + + +
not_so_random + +
golden_features + +
insert_random_feature + +
feature_selection + +
hill_climbing_1 + +
hill_climbing_2 + +
ensemble + + +
stack +
ensemble_stacked +

from docs.

pplonski avatar pplonski commented on May 29, 2024

Thank you @aplonska ! That's what I need!

from docs.

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