Welcome to SKSurrogate’s documentation!

Contents:

• Introduction
  • Dependencies
  • Download
  • Installation
  • Documentation
  • License
    • MIT License
• Surrogate-Based Optimization
  • Sampling
    • CompactSample
    • BoxSample
    • SphereSample
  • Surrogate models
  • Optimizer
• Hyperparameter Optimization
• Hilbert Spaces
  • Orthonormal system of functions
• Sensitivity Analysis
  • Morris
  • Sobol
  • Moment-Independent \(\delta\) Index
• Eliminate features based on Pearson correlation
• Evolutionary Optimization Algorithms
  • A General Evolutionary Optimization Algorithm
    • Example
• Optimized Pipeline Detector
  • Some Technical Notes
    • Stacking
    • Permutation Importance
    • imblearn pipelines
    • Categorical Variables
• A machine learning progress tracker
  • SVM Classifier with RBF v.s. SGDClassifier with Kernels
• Code Documentation
  • Surrogate Random Search
  • Evolutionary Optimization Algorithm
  • Hilbert Space based regression
  • Sensitivity Analysis
  • Optimized Pipeline Detector
  • MLTrace: A machine learning progress tracker
  • synthdata Module
    • Supported data types
    • Generating Synthetic Data
    • Constraints
    • Code documentation

Indices and tables

• Index
• Module Index
• Search Page