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Contents:

  • Installing julearn
  • Input Data
  • Understanding the pipeline
  • Scoring
  • Available Pipeline Steps
  • Hyperparameters
  • Basic Examples
    • Parallelize Julearn
    • Simple Binary Classification
    • Inspecting Random Forest models
    • Multiclass Classification
    • Inspecting SVM models
    • Stratified K-fold CV for regression analysis
    • Preprocessing with variance threshold, zscore and PCA
    • Regression Analysis
    • Confound Removal (model comparison)
  • Advanced Examples
  • Reference
  • Contributing to julearn
  • Maintaining julearn
  • What’s new
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  • Basic Examples
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Basic Examples

Parallelize Julearn

Parallelize Julearn

Simple Binary Classification

Simple Binary Classification

Inspecting Random Forest models

Inspecting Random Forest models

Multiclass Classification

Multiclass Classification

Inspecting SVM models

Inspecting SVM models

Stratified K-fold CV for regression analysis

Stratified K-fold CV for regression analysis

Preprocessing with variance threshold, zscore and PCA

Preprocessing with variance threshold, zscore and PCA

Regression Analysis

Regression Analysis

Confound Removal (model comparison)

Confound Removal (model comparison)

Download all examples in Python source code: basic_python.zip

Download all examples in Jupyter notebooks: basic_jupyter.zip

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