Model Tuner
Getting Started
Welcome to Model Tuner’s Documentation!
Usage Guide
iPython Notebooks
Key Methods and Functionalities
Helper Functions
Input Parameters
Pipeline Management
Binary Classification
Regression
Bootstrap Metrics
Caveats
Zero Variance Columns
Dependent Variable
Imputation Before Scaling
Column Stratification with Cross-Validation
Model Calibration
Using Imputation and Scaling in Pipeline Steps for Model Preprocessing
Caveats in Imbalanced Learning
ElasticNet Regularization
About Model Tuner
GitHub Repository
Acknowledgements
Citing Model Tuner
Changelog
References
Model Tuner
Index
Index
B
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C
|
E
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G
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M
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R
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S
B
built-in function
check_input_type()
evaluate_bootstrap_metrics()
get_feature_selection_pipeline()
get_preprocessing_and_feature_selection_pipeline()
get_preprocessing_pipeline()
return_bootstrap_metrics()
sampling_method()
C
check_input_type()
built-in function
E
evaluate_bootstrap_metrics()
built-in function
G
get_feature_selection_pipeline()
built-in function
get_preprocessing_and_feature_selection_pipeline()
built-in function
get_preprocessing_pipeline()
built-in function
M
Model (built-in class)
R
return_bootstrap_metrics()
built-in function
S
sampling_method()
built-in function