Run
1860378

Run 1860378

Task 248 (Supervised Classification) mfeat-morphological Uploaded 27-03-2017 by Randal Olson
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  • Mon_Mar_27_15.10.49_2017 NumPy_1.11.3. Python_3.6.0. run_task SciPy_0.19.0. sklearn.pipeline.Pipeline Sklearn_0.18.1.
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Flow

sklearn.pipeline.Pipeline(pca=sklearn.decomposition.pca.PCA,randomforestcla ssifier=sklearn.ensemble.forest.RandomForestClassifier)(1)Automatically created scikit-learn flow.
sklearn.ensemble.forest.RandomForestClassifier(16)_bootstrapTrue
sklearn.ensemble.forest.RandomForestClassifier(16)_class_weightNone
sklearn.ensemble.forest.RandomForestClassifier(16)_criteriongini
sklearn.ensemble.forest.RandomForestClassifier(16)_max_depthNone
sklearn.ensemble.forest.RandomForestClassifier(16)_max_featuresauto
sklearn.ensemble.forest.RandomForestClassifier(16)_max_leaf_nodesNone
sklearn.ensemble.forest.RandomForestClassifier(16)_min_impurity_split1e-07
sklearn.ensemble.forest.RandomForestClassifier(16)_min_samples_leaf1
sklearn.ensemble.forest.RandomForestClassifier(16)_min_samples_split2
sklearn.ensemble.forest.RandomForestClassifier(16)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(16)_n_estimators500
sklearn.ensemble.forest.RandomForestClassifier(16)_n_jobs-1
sklearn.ensemble.forest.RandomForestClassifier(16)_oob_scoreFalse
sklearn.ensemble.forest.RandomForestClassifier(16)_random_stateNone
sklearn.ensemble.forest.RandomForestClassifier(16)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(16)_warm_startFalse
sklearn.decomposition.pca.PCA(1)_copyTrue
sklearn.decomposition.pca.PCA(1)_iterated_powerauto
sklearn.decomposition.pca.PCA(1)_n_componentsNone
sklearn.decomposition.pca.PCA(1)_random_stateNone
sklearn.decomposition.pca.PCA(1)_svd_solverauto
sklearn.decomposition.pca.PCA(1)_tol0.0
sklearn.decomposition.pca.PCA(1)_whitenFalse
sklearn.pipeline.Pipeline(pca=sklearn.decomposition.pca.PCA,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(1)_steps[('pca', PCA(copy=True, iterated_power='auto', n_components=None, random_state=None, svd_solver='auto', tol=0.0, whiten=False)), ('randomforestclassifier', RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini', max_depth=None, max_features='auto', max_leaf_nodes=None, min_impurity_split=1e-07, min_samples_leaf=1, min_samples_split=2, min_weight_fraction_leaf=0.0, n_estimators=500, n_jobs=-1, oob_score=False, random_state=None, verbose=0, warm_start=False))]

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
0.96
Per class
Cross-validation details (33% Holdout set)
F measure
0.7111
Per class
Cross-validation details (33% Holdout set)
Kappa
0.6832
Cross-validation details (33% Holdout set)
KB relative information score
487.8306
Cross-validation details (33% Holdout set)
Mean absolute error
0.0674
Cross-validation details (33% Holdout set)
Mean prior absolute error
0.18
Cross-validation details (33% Holdout set)
Number of instances
660
Per class
Cross-validation details (33% Holdout set)
Precision
0.7104
Per class
Cross-validation details (33% Holdout set)
Predictive accuracy
0.7152
Cross-validation details (33% Holdout set)
Prior entropy
3.3219
Cross-validation details (33% Holdout set)
Recall
0.7152
Per class
Cross-validation details (33% Holdout set)
Relative absolute error
0.3746
Cross-validation details (33% Holdout set)
Root mean prior squared error
0.3
Cross-validation details (33% Holdout set)
Root mean squared error
0.193
Cross-validation details (33% Holdout set)
Root relative squared error
0.6433
Cross-validation details (33% Holdout set)