README.md

Summary of 1_Default_LightGBM

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LightGBM

• n_jobs: -1
• objective: binary
• num_leaves: 63
• learning_rate: 0.05
• feature_fraction: 0.9
• bagging_fraction: 0.9
• min_data_in_leaf: 10
• metric: binary_logloss
• custom_eval_metric_name: None
• explain_level: 2

Validation

• validation_type: split
• train_ratio: 0.75
• shuffle: True
• stratify: True

Optimized metric

logloss

Training time

11.2 seconds

Metric details

	score	threshold
logloss	0.612197	nan
auc	0.722196	nan
f1	0.696209	0.321122
accuracy	0.658612	0.524822
precision	0.823529	0.812509
recall	1	0.0306004
mcc	0.324938	0.428667

Confusion matrix (at threshold=0.524822)

	Predicted as 0	Predicted as 1
Labeled as 0	570	251
Labeled as 1	300	493

Learning curves

Permutation-based Importance

Confusion Matrix

Normalized Confusion Matrix

ROC Curve

Kolmogorov-Smirnov Statistic

Precision-Recall Curve

Calibration Curve

Cumulative Gains Curve

Lift Curve

SHAP Importance

SHAP Dependence plots

Dependence (Fold 1)

SHAP Decision plots

Top-10 Worst decisions for class 0 (Fold 1)

Top-10 Best decisions for class 0 (Fold 1)

Top-10 Worst decisions for class 1 (Fold 1)

Top-10 Best decisions for class 1 (Fold 1)

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