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julearn documentation
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julearn documentation
  • 1. Getting started
  • 2. Setup suggestion
  • 3. Installing
  • 4. Optional Dependencies
  • 5. What you really need to know
    • 5.1. Why cross validation?
    • 5.2. Data
    • 5.3. Model Building
    • 5.4. Model Evaluation
    • 5.5. Model Comparison
  • 6. Selected deeper topics
    • 6.1. Applying preprocessing to the target
    • 6.2. Cross-validation consistent Confound Removal
    • 6.3. Hyperparameter Tuning
    • 6.4. Inspecting Models
    • 6.5. Cross-validation splitters
    • 6.6. Stacking Models
    • 6.7. Connectome-based Predictive Modeling (CBPM)
  • 7. Overview of available Pipeline Steps
  • 8. Examples
    • 8.1. Starting with julearn
      • Working with pandas
      • Simple Binary Classification
      • Grouped CV
      • Multiclass Classification
      • Stratified K-fold CV for regression analysis
      • Regression Analysis
    • 8.2. Model Comparison
      • Simple Model Comparison
    • 8.3. Inspection
      • Inspecting the fold-wise predictions
      • Inspecting Random Forest models
      • Inspecting SVM models
      • Preprocessing with variance threshold, zscore and PCA
    • 8.4. Complex Models
      • Transforming target variable with z-score
      • Tuning Hyperparameters using Bayesian Search
      • Tuning Multiple Hyperparameters Grids
      • Stacking Classification
      • Tuning Hyperparameters
      • Regression Analysis
    • 8.5. Confounds
      • Return Confounds in Confound Removal
      • Confound Removal (model comparison)
    • 8.6. Customization
      • Custom Scoring Function for Regression
  • 9. API Reference
    • 9.1. Main API
      • julearn.run_cross_validation
    • 9.2. Pipeline
      • julearn.PipelineCreator
      • julearn.TargetPipelineCreator
      • julearn.pipeline.JuTargetPipeline
      • julearn.pipeline.pipeline_creator.Step
    • 9.3. Model Selection
      • julearn.model_selection.ContinuousStratifiedKFold
      • julearn.model_selection.RepeatedContinuousStratifiedKFold
      • julearn.model_selection.ContinuousStratifiedGroupKFold
      • julearn.model_selection.RepeatedContinuousStratifiedGroupKFold
      • julearn.model_selection.StratifiedBootstrap
      • julearn.model_selection.get_searcher
      • julearn.model_selection.list_searchers
      • julearn.model_selection.register_searcher
      • julearn.model_selection.reset_searcher_register
    • 9.4. Base
      • julearn.base.JuBaseEstimator
      • julearn.base.JuTransformer
      • julearn.base.WrapModel
      • julearn.base.ColumnTypes
      • julearn.base.ColumnTypesLike
      • julearn.base.change_column_type
      • julearn.base.get_column_type
      • julearn.base.make_type_selector
      • julearn.base.ensure_column_types
    • 9.5. Inspect
      • julearn.inspect.Inspector
      • julearn.inspect.FoldsInspector
      • julearn.inspect.preprocess
    • 9.6. Models
      • julearn.models.list_models
      • julearn.models.get_model
      • julearn.models.register_model
      • julearn.models.reset_model_register
    • 9.7. Dynamic Selection (DESLib)
      • julearn.models.dynamic.DynamicSelection
    • 9.8. Scoring
      • julearn.scoring.get_scorer
      • julearn.scoring.list_scorers
      • julearn.scoring.register_scorer
      • julearn.scoring.reset_scorer_register
      • julearn.scoring.check_scoring
    • 9.9. Scoring Metrics
      • julearn.scoring.metrics.r_corr
      • julearn.scoring.metrics.r2_corr
    • 9.10. Transformers
      • julearn.transformers.DropColumns
      • julearn.transformers.ChangeColumnTypes
      • julearn.transformers.SetColumnTypes
      • julearn.transformers.FilterColumns
      • julearn.transformers.CBPM
      • julearn.transformers.JuColumnTransformer
      • julearn.transformers.confound_remover.ConfoundRemover
      • julearn.transformers.list_transformers
      • julearn.transformers.get_transformer
      • julearn.transformers.register_transformer
      • julearn.transformers.reset_transformer_register
    • 9.11. Target Transformers
      • julearn.transformers.target.JuTransformedTargetModel
      • julearn.transformers.target.JuTargetTransformer
      • julearn.transformers.target.TargetConfoundRemover
      • julearn.transformers.target.TransformedTargetWarning
      • julearn.transformers.target.get_target_transformer
      • julearn.transformers.target.list_target_transformers
      • julearn.transformers.target.register_target_transformer
      • julearn.transformers.target.reset_target_transformer_register
    • 9.12. Utils
      • julearn.utils.logger
      • julearn.utils.configure_logging
      • julearn.utils.raise_error
      • julearn.utils.warn_with_log
    • 9.13. Typing
      • julearn.utils.typing.JuEstimatorLike
      • julearn.utils.typing.EstimatorLike
      • julearn.utils.typing.EstimatorLikeFit1
      • julearn.utils.typing.EstimatorLikeFit2
      • julearn.utils.typing.EstimatorLikeFity
    • 9.14. Prepare
      • julearn.prepare.prepare_input_data
      • julearn.prepare.check_consistency
    • 9.15. Stats
      • julearn.stats.corrected_ttest
    • 9.16. Visualization
      • julearn.viz.plot_scores
  • 10. Configuring julearn
  • 11. Contributing
  • 12. Maintaining
  • 13. FAQs
  • 14. What’s new
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8.4. Complex Models#

Examples that show how to build complex models.

Transforming target variable with z-score

Transforming target variable with z-score

Tuning Hyperparameters using Bayesian Search

Tuning Hyperparameters using Bayesian Search

Tuning Multiple Hyperparameters Grids

Tuning Multiple Hyperparameters Grids

Stacking Classification

Stacking Classification

Tuning Hyperparameters

Tuning Hyperparameters

Regression Analysis

Regression Analysis

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