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Introduction

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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

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