PHOTONAI Wizard

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PHOTONAI Wizard

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Basic
Standard Classifier

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Dimensionality Reduction

Estimator Selection

Feature Selection

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    Transformers

    LabelEncoder
    SimpleImputer missing_values np.nan
    strategy mean
    fill_value 0
    PCA n_components 0.8

    Estimators

    RandomForestClassifier n_estimators 50
    criterion gini
    max_depth None
    min_samples_split 2
    min_samples_leaf 1

Optimized
Standard Classifier

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Dimensionality Reduction

Estimator Selection

Feature Selection

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    Transformers

    LabelEncoder
    SimpleImputer missing_values np.nan
    strategy mean
    fill_value 0
    PCA n_components FloatRange(0.2, 0.99)

    Estimators

    RandomForestClassifier n_estimators [25, 50, 75]
    criterion gini
    max_depth None
    min_samples_split IntegerRange(2, 10)
    min_samples_leaf IntegerRange(1, 10)

Basic
Feature Selection Classification

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Dimensionality Reduction

Estimator Selection

Feature Selection

  • Show Pipeline Elements

    Transformers

    LabelEncoder
    SimpleImputer missing_values np.nan
    strategy mean
    fill_value 0
    PCA n_components 0.8

    Estimators

    RandomForestClassifier n_estimators 50
    criterion gini
    max_depth None
    min_samples_split 2
    min_samples_leaf 1
    GaussianProcessClassifier optimizer fmin_l_bfgs_b
    n_restarts_optimizer 0
    AdaBoostClassifier n_estimators 50
    learning_rate 1
    SVC C 1
    gamma scale
    max_iter 1000000.0
    kernel linear

Optimized
Feature Selection Classification

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Dimensionality Reduction

Estimator Selection

Feature Selection

  • Show Pipeline Elements

    Transformers

    LabelEncoder
    SimpleImputer missing_values np.nan
    strategy mean
    fill_value 0
    PCA n_components FloatRange(0.2, 0.99)

    Estimators

    RandomForestClassifier n_estimators [25, 50, 75]
    criterion gini
    max_depth None
    min_samples_split IntegerRange(2, 10)
    min_samples_leaf IntegerRange(1, 10)
    GaussianProcessClassifier optimizer fmin_l_bfgs_b
    n_restarts_optimizer 0
    AdaBoostClassifier n_estimators IntegerRange(30, 80)
    learning_rate FloatRange(0.1, 1)
    SVC C FloatRange(1e-7, 1e7, range_type="geomspace")
    gamma scale
    max_iter 1000000.0
    kernel ['linear', 'rbf']

Basic
Classifier Selection

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Dimensionality Reduction

Estimator Selection

Feature Selection

  • Show Pipeline Elements

    Transformers

    LabelEncoder
    SimpleImputer missing_values np.nan
    strategy mean
    fill_value 0
    FClassifSelectPercentile percentile 25

    Estimators

    SVC C 1
    gamma scale
    max_iter 1000000.0
    kernel linear

Optimized
Classifier Selection

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Dimensionality Reduction

Estimator Selection

Feature Selection

  • Show Pipeline Elements

    Transformers

    LabelEncoder
    SimpleImputer missing_values np.nan
    strategy mean
    fill_value 0
    FClassifSelectPercentile percentile [10, 25, 50, 75]

    Estimators

    SVC C FloatRange(1e-7, 1e7, range_type="geomspace")
    gamma scale
    max_iter 1000000.0
    kernel ['linear', 'rbf']

Basic
Feature and Classifier Selection

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Dimensionality Reduction

Estimator Selection

Feature Selection

  • Show Pipeline Elements

    Transformers

    LabelEncoder
    SimpleImputer missing_values np.nan
    strategy mean
    fill_value 0
    FClassifSelectPercentile percentile 25

    Estimators

    SVC C 1
    gamma scale
    max_iter 1000000.0
    kernel linear
    RandomForestClassifier n_estimators 50
    criterion gini
    max_depth None
    min_samples_split 2
    min_samples_leaf 1
    AdaBoostClassifier n_estimators 50
    learning_rate 1
    GaussianProcessClassifier optimizer fmin_l_bfgs_b
    n_restarts_optimizer 0

Optimized
Feature and Classifier Selection

Select Pipeline

Dimensionality Reduction

Estimator Selection

Feature Selection

  • Show Pipeline Elements

    Transformers

    LabelEncoder
    SimpleImputer missing_values np.nan
    strategy mean
    fill_value 0
    FClassifSelectPercentile percentile [10, 25, 50, 75]

    Estimators

    SVC C FloatRange(1e-7, 1e7, range_type="geomspace")
    gamma scale
    max_iter 1000000.0
    kernel ['linear', 'rbf']
    RandomForestClassifier n_estimators [25, 50, 75]
    criterion gini
    max_depth None
    min_samples_split IntegerRange(2, 10)
    min_samples_leaf IntegerRange(1, 10)
    AdaBoostClassifier n_estimators IntegerRange(30, 80)
    learning_rate FloatRange(0.1, 1)
    GaussianProcessClassifier optimizer fmin_l_bfgs_b
    n_restarts_optimizer 0

Basic
Standard Regressor

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Dimensionality Reduction

Estimator Selection

Feature Selection

  • Show Pipeline Elements

    Transformers

    SimpleImputer missing_values np.nan
    strategy mean
    fill_value 0
    PCA n_components 0.8

    Estimators

    RandomForestRegressor n_estimators 50
    criterion mse
    max_depth None
    min_samples_split 2
    min_samples_leaf 1

Optimized
Standard Regressor

Select Pipeline

Dimensionality Reduction

Estimator Selection

Feature Selection

  • Show Pipeline Elements

    Transformers

    SimpleImputer missing_values np.nan
    strategy mean
    fill_value 0
    PCA n_components FloatRange(0.2, 0.99)

    Estimators

    RandomForestRegressor n_estimators [25, 50, 75]
    criterion mse
    max_depth None
    min_samples_split IntegerRange(2, 10)
    min_samples_leaf IntegerRange(1, 10)

Basic
Feature Selection Regression

Select Pipeline

Dimensionality Reduction

Estimator Selection

Feature Selection

  • Show Pipeline Elements

    Transformers

    SimpleImputer missing_values np.nan
    strategy mean
    fill_value 0
    PCA n_components 0.8

    Estimators

    RandomForestRegressor n_estimators 50
    criterion mse
    max_depth None
    min_samples_split 2
    min_samples_leaf 1
    GaussianProcessRegressor optimizer fmin_l_bfgs_b
    n_restarts_optimizer 0
    alpha 1e-10
    AdaBoostRegressor n_estimators 50
    learning_rate 1
    loss linear
    SVR C 1
    gamma scale
    max_iter 1000000.0
    kernel linear
    epsilon 0.1

Optimized
Feature Selection Regression

Select Pipeline

Dimensionality Reduction

Estimator Selection

Feature Selection

  • Show Pipeline Elements

    Transformers

    SimpleImputer missing_values np.nan
    strategy mean
    fill_value 0
    PCA n_components FloatRange(0.2, 0.99)

    Estimators

    RandomForestRegressor n_estimators [25, 50, 75]
    criterion mse
    max_depth None
    min_samples_split IntegerRange(2, 10)
    min_samples_leaf IntegerRange(1, 10)
    GaussianProcessRegressor optimizer fmin_l_bfgs_b
    n_restarts_optimizer 0
    alpha 1e-10
    AdaBoostRegressor n_estimators IntegerRange(30, 80)
    learning_rate FloatRange(0.1, 1)
    loss linear
    SVR C FloatRange(1e-7, 1e7, range_type="geomspace")
    gamma scale
    max_iter 1000000.0
    kernel ['linear', 'rbf']
    epsilon 0.1

Basic
Regressor Selection

Select Pipeline

Dimensionality Reduction

Estimator Selection

Feature Selection

  • Show Pipeline Elements

    Transformers

    SimpleImputer missing_values np.nan
    strategy mean
    fill_value 0
    FRegressionSelectPercentile percentile 25

    Estimators

    SVR C 1
    gamma scale
    max_iter 1000000.0
    kernel linear
    epsilon 0.1

Optimized
Regressor Selection

Select Pipeline

Dimensionality Reduction

Estimator Selection

Feature Selection

  • Show Pipeline Elements

    Transformers

    SimpleImputer missing_values np.nan
    strategy mean
    fill_value 0
    FRegressionSelectPercentile percentile [10, 25, 50, 75]

    Estimators

    SVR C FloatRange(1e-7, 1e7, range_type="geomspace")
    gamma scale
    max_iter 1000000.0
    kernel ['linear', 'rbf']
    epsilon 0.1

Basic
Feature and Regressor Selection

Select Pipeline

Dimensionality Reduction

Estimator Selection

Feature Selection

  • Show Pipeline Elements

    Transformers

    SimpleImputer missing_values np.nan
    strategy mean
    fill_value 0
    FRegressionSelectPercentile percentile 25

    Estimators

    SVR C 1
    gamma scale
    max_iter 1000000.0
    kernel linear
    epsilon 0.1
    RandomForestRegressor n_estimators 50
    criterion mse
    max_depth None
    min_samples_split 2
    min_samples_leaf 1
    AdaBoostRegressor n_estimators 50
    learning_rate 1
    loss linear
    GaussianProcessRegressor optimizer fmin_l_bfgs_b
    n_restarts_optimizer 0
    alpha 1e-10

Optimized
Feature and Regressor Selection

Select Pipeline

Dimensionality Reduction

Estimator Selection

Feature Selection

  • Show Pipeline Elements

    Transformers

    SimpleImputer missing_values np.nan
    strategy mean
    fill_value 0
    FRegressionSelectPercentile percentile [10, 25, 50, 75]

    Estimators

    SVR C FloatRange(1e-7, 1e7, range_type="geomspace")
    gamma scale
    max_iter 1000000.0
    kernel ['linear', 'rbf']
    epsilon 0.1
    RandomForestRegressor n_estimators [25, 50, 75]
    criterion mse
    max_depth None
    min_samples_split IntegerRange(2, 10)
    min_samples_leaf IntegerRange(1, 10)
    AdaBoostRegressor n_estimators IntegerRange(30, 80)
    learning_rate FloatRange(0.1, 1)
    loss linear
    GaussianProcessRegressor optimizer fmin_l_bfgs_b
    n_restarts_optimizer 0
    alpha 1e-10

Basic
Neuro Standard Classification

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Dimensionality Reduction

Estimator Selection

Feature Selection

  • Show Pipeline Elements

    Neuro Transformers

    MNI_ICBM152_GrayMatter

    Transformers

    LabelEncoder
    PCA n_components 0.8

    Estimators

    SVC C 1
    gamma scale
    max_iter 1000000.0
    kernel linear

Optimized
Neuro Standard Classification

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Dimensionality Reduction

Estimator Selection

Feature Selection

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    Neuro Transformers

    MNI_ICBM152_GrayMatter

    Transformers

    LabelEncoder
    PCA n_components FloatRange(0.2, 0.99)

    Estimators

    SVC C FloatRange(1e-7, 1e7, range_type="geomspace")
    gamma scale
    max_iter 1000000.0
    kernel ['linear', 'rbf']

Basic
Neuro Cortical Classification

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Dimensionality Reduction

Estimator Selection

Feature Selection

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    Neuro Transformers

    HarvardOxford_Cortical_Threshold_25 roi_names ['all']

    Transformers

    LabelEncoder
    PCA n_components 0.8

    Estimators

    SVC C 1
    gamma scale
    max_iter 1000000.0
    kernel linear

Optimized
Neuro Cortical Classification

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Dimensionality Reduction

Estimator Selection

Feature Selection

  • Show Pipeline Elements

    Neuro Transformers

    HarvardOxford_Cortical_Threshold_25 roi_names ['all']

    Transformers

    LabelEncoder
    PCA n_components FloatRange(0.2, 0.99)

    Estimators

    SVC C FloatRange(1e-7, 1e7, range_type="geomspace")
    gamma scale
    max_iter 1000000.0
    kernel ['linear', 'rbf']

Basic
Neuro Standard Regression

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Dimensionality Reduction

Estimator Selection

Feature Selection

  • Show Pipeline Elements

    Neuro Transformers

    MNI_ICBM152_GrayMatter

    Transformers

    PCA n_components 0.8

    Estimators

    SVR C 1
    gamma scale
    max_iter 1000000.0
    kernel linear
    epsilon 0.1

Optimized
Neuro Standard Regression

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Dimensionality Reduction

Estimator Selection

Feature Selection

  • Show Pipeline Elements

    Neuro Transformers

    MNI_ICBM152_GrayMatter

    Transformers

    PCA n_components FloatRange(0.2, 0.99)

    Estimators

    SVR C FloatRange(1e-7, 1e7, range_type="geomspace")
    gamma scale
    max_iter 1000000.0
    kernel ['linear', 'rbf']
    epsilon 0.1

Basic
Neuro Cortical Regression

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Dimensionality Reduction

Estimator Selection

Feature Selection

  • Show Pipeline Elements

    Neuro Transformers

    HarvardOxford_Cortical_Threshold_25 roi_names ['all']

    Transformers

    PCA n_components 0.8

    Estimators

    SVR C 1
    gamma scale
    max_iter 1000000.0
    kernel linear
    epsilon 0.1

Optimized
Neuro Cortical Regression

Select Pipeline

Dimensionality Reduction

Estimator Selection

Feature Selection

  • Show Pipeline Elements

    Neuro Transformers

    HarvardOxford_Cortical_Threshold_25 roi_names ['all']

    Transformers

    PCA n_components FloatRange(0.2, 0.99)

    Estimators

    SVR C FloatRange(1e-7, 1e7, range_type="geomspace")
    gamma scale
    max_iter 1000000.0
    kernel ['linear', 'rbf']
    epsilon 0.1

PHOTON SYNTAX