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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)
    • 6.8. Parallelizing julearn with Joblib
  • 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
      • Target Generation
      • Transforming target variable with z-score
      • Tuning Multiple Hyperparameters Grids
      • Tuning Hyperparameters using Bayesian Search
      • 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
      • julearn.run_fit
    • 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.final_model_cv._JulearnFinalModelCV
      • 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.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.PipelineInspector
      • julearn.inspect.preprocess
    • 9.6. Models
      • julearn.models.list_models
      • julearn.models.get_model
      • julearn.models.register_model
      • julearn.models.reset_model_register
      • julearn.models.xgb_cvearlystopping.XGBClassifierCVEarlyStopping
      • julearn.models.xgb_cvearlystopping.XGBRegressorCVEarlyStopping
    • 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.DataLike
      • julearn.utils.typing.ScorerLike
      • julearn.utils.typing.EstimatorLike
      • julearn.utils.typing.CVLike
      • julearn.utils.typing.ColumnTypesLike
      • julearn.utils.typing.EstimatorLikeFit1
      • julearn.utils.typing.EstimatorLikeFit2
      • julearn.utils.typing.EstimatorLikeFity
      • julearn.utils.typing.TransformerLike
      • julearn.utils.typing.ModelLike
      • julearn.utils.typing.JuEstimatorLike
      • julearn.utils.typing.JuModelLike
    • 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
    • 9.17. Config
      • julearn.config.set_config
      • julearn.config.get_config
  • 10. Configuring julearn
  • 11. Contributing
  • 12. Maintaining
  • 13. FAQs
  • 14. What’s new
main (dev)
  • v0.3.5 (latest)
  • v0.3.4
  • v0.3.3
  • v0.3.2
  • v0.3.1
  • v0.3.0
  • v0.2.7
  • v0.2.5
  • v0.2.4
  • v0.2.3
  • v0.2.2
  • main (dev)
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Note

This page is a reference documentation. It only explains the function signature, and not how to use it. Please refer to the What you really need to know section for the big picture.

julearn.utils.typing.EstimatorLike¶

type julearn.utils.typing.EstimatorLike = EstimatorLikeFit1 | EstimatorLikeFit2 | EstimatorLikeFity¶
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  • julearn.utils.typing.EstimatorLike
    • EstimatorLike