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sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(preprocessing=sklearn.preprocessing.data.RobustScaler,dimension_reduction=sklearn.decomposition.pca.PCA,classifier=sklearn.neighbors.classification.KNeighborsClassifier))

sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(preprocessing=sklearn.preprocessing.data.RobustScaler,dimension_reduction=sklearn.decomposition.pca.PCA,classifier=sklearn.neighbors.classification.KNeighborsClassifier))

Visibility: public Uploaded 10-03-2018 by Gabriel Price sklearn==0.19.1 numpy>=1.6.1 scipy>=0.9 6 runs
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Automatically created scikit-learn flow.

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estimator

sklearn.pipeline.Pipeline(preprocessing=sklearn.preprocessing.data.RobustScaler,dimension_reduction=sklearn.decomposition.pca.PCA,classifier=sklearn.neighbors.classification.KNeighborsClassifier)(1)

Parameters

cv		default: 5
error_score		default: "raise"
estimator		default: {"oml-python:serialized_object": "component_reference", "value": {"key": "estimator", "step_name": null}}
fit_params		default: null
iid		default: true
n_jobs		default: 1
param_grid		default: {"classifier__n_neighbors": [1, 2, 3, 4, 5, 6, 8, 9, 10], "dimension_reduction__n_components": [50, 100, 140, 145, 150, 155, 160, 200, 250, 300]}
pre_dispatch		default: "2*n_jobs"
refit		default: true
return_train_score		default: "warn"
scoring		default: null
verbose		default: 0

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sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(preprocessing=sklearn.preprocessing.data.RobustScaler,dimension_reduction=sklearn.decomposition.pca.PCA,classifier=sklearn.neighbors.classification.KNeighborsClassifier))

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