Model Tuner

Getting Started

  • Welcome to Model Tuner’s Documentation!

Usage Guide

  • iPython Notebooks
  • Input Parameters
  • Key Methods and Functionalities
  • Helper Functions
  • Pipeline Management
  • Binary Classification
  • Multi-Class Classification
  • Regression
  • Performance Evaluation Metrics
  • Bootstrap Metrics

Caveats

  • Zero Variance Columns
  • Dependent Variable
  • Scaling Before Imputation
  • Column Stratification with Cross-Validation
  • Model Calibration
  • Using Imputation and Scaling in Pipeline Steps for Model Preprocessing
  • Caveats in Imbalanced Learning
  • Threshold Tuning Considerations
  • ElasticNet Regularization
  • CatBoost Training Parameters

About Model Tuner

  • GitHub Repository
  • Acknowledgements
  • Citing Model Tuner
  • Changelog
  • References
Model Tuner
  • Search

© Copyright 2024, UCLA CTSI ML Team: Leonid Shpaner, Arthur Funnell, Panayiotis Petousis.

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