Run
1849113

Run 1849113

Task 145677 (Supervised Classification) Bioresponse Uploaded 07-03-2017 by Stefan Majoor
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  • NumPy_1.12.0. Python_3.5.2. run_task SciPy_0.18.1. sklearn.pipeline.Pipeline Sklearn_0.18.1. Tue_Mar__7_18.38.55_2017
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.Pipeline(scaling=sklearn.preprocessing.data.StandardScaler ,selector=sklearn.feature_selection.univariate_selection.GenericUnivariateS elect,classifier=sklearn.neighbors.classification.KNeighborsClassifier)(1)Automatically created scikit-learn flow.
sklearn.neighbors.classification.KNeighborsClassifier(7)_algorithmbrute
sklearn.neighbors.classification.KNeighborsClassifier(7)_leaf_size1
sklearn.neighbors.classification.KNeighborsClassifier(7)_metricminkowski
sklearn.neighbors.classification.KNeighborsClassifier(7)_metric_paramsNone
sklearn.neighbors.classification.KNeighborsClassifier(7)_n_jobs-1
sklearn.neighbors.classification.KNeighborsClassifier(7)_n_neighbors10
sklearn.neighbors.classification.KNeighborsClassifier(7)_p2
sklearn.neighbors.classification.KNeighborsClassifier(7)_weightsuniform
sklearn.preprocessing.data.StandardScaler(1)_copyTrue
sklearn.preprocessing.data.StandardScaler(1)_with_meanTrue
sklearn.preprocessing.data.StandardScaler(1)_with_stdTrue
sklearn.feature_selection.univariate_selection.GenericUnivariateSelect(1)_modek_best
sklearn.feature_selection.univariate_selection.GenericUnivariateSelect(1)_param170
sklearn.feature_selection.univariate_selection.GenericUnivariateSelect(1)_score_func
sklearn.pipeline.Pipeline(scaling=sklearn.preprocessing.data.StandardScaler,selector=sklearn.feature_selection.univariate_selection.GenericUnivariateSelect,classifier=sklearn.neighbors.classification.KNeighborsClassifier)(1)_steps[('scaling', StandardScaler(copy=True, with_mean=True, with_std=True)), ('selector', GenericUnivariateSelect(mode='k_best', param=170, score_func=)), ('classifier', KNeighborsClassifier(algorithm='brute', leaf_size=1, metric='minkowski', metric_params=None, n_jobs=-1, n_neighbors=10, p=2, weights='uniform'))]

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

17 Evaluation measures

Area under ROC curve
0.8388
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7651
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.5277
Cross-validation details (10-fold Crossvalidation)
KB relative information score
1526.6157
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3056
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4964
Cross-validation details (10-fold Crossvalidation)
Number of instances
3751
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.7658
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7649
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9948
Cross-validation details (10-fold Crossvalidation)
Recall
0.7649
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.6155
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4982
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4035
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.8098
Cross-validation details (10-fold Crossvalidation)