Run
8886087

Run 8886087

Task 167133 (Supervised Classification) CIFAR_10_small Uploaded 16-03-2018 by jiawen wang
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Flow

sklearn.pipeline.Pipeline(preprocessing=sklearn.preprocessing.data.Standard Scaler,feature=sklearn.feature_selection.univariate_selection.SelectKBest,c lassifier=sklearn.ensemble.forest.RandomForestClassifier)(1)Automatically created scikit-learn flow.
sklearn.preprocessing.data.StandardScaler(5)_copytrue
sklearn.preprocessing.data.StandardScaler(5)_with_meantrue
sklearn.preprocessing.data.StandardScaler(5)_with_stdtrue
sklearn.ensemble.forest.RandomForestClassifier(32)_bootstraptrue
sklearn.ensemble.forest.RandomForestClassifier(32)_class_weightnull
sklearn.ensemble.forest.RandomForestClassifier(32)_criterion"gini"
sklearn.ensemble.forest.RandomForestClassifier(32)_max_depthnull
sklearn.ensemble.forest.RandomForestClassifier(32)_max_featuresnull
sklearn.ensemble.forest.RandomForestClassifier(32)_max_leaf_nodesnull
sklearn.ensemble.forest.RandomForestClassifier(32)_min_impurity_decrease0.0
sklearn.ensemble.forest.RandomForestClassifier(32)_min_impurity_splitnull
sklearn.ensemble.forest.RandomForestClassifier(32)_min_samples_leaf1
sklearn.ensemble.forest.RandomForestClassifier(32)_min_samples_split2
sklearn.ensemble.forest.RandomForestClassifier(32)_min_weight_fraction_leaf0.0
sklearn.ensemble.forest.RandomForestClassifier(32)_n_estimators200
sklearn.ensemble.forest.RandomForestClassifier(32)_n_jobs-1
sklearn.ensemble.forest.RandomForestClassifier(32)_oob_scorefalse
sklearn.ensemble.forest.RandomForestClassifier(32)_random_state43256
sklearn.ensemble.forest.RandomForestClassifier(32)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(32)_warm_startfalse
sklearn.feature_selection.univariate_selection.SelectKBest(2)_k100
sklearn.feature_selection.univariate_selection.SelectKBest(2)_score_func{"oml-python:serialized_object": "function", "value": "sklearn.feature_selection.univariate_selection.f_classif"}
sklearn.pipeline.Pipeline(preprocessing=sklearn.preprocessing.data.StandardScaler,feature=sklearn.feature_selection.univariate_selection.SelectKBest,classifier=sklearn.ensemble.forest.RandomForestClassifier)(1)_memorynull

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
0.7176 ± 0.0073
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.2514 ± 0.0083
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.1749 ± 0.0095
Cross-validation details (10-fold Crossvalidation)
KB relative information score
3829.1255 ± 7.1231
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1668 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.18 ± 0
Cross-validation details (10-fold Crossvalidation)
Number of instances
20000
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.2531 ± 0.0086
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.2575 ± 0.0086
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3218
Cross-validation details (10-fold Crossvalidation)
Recall
0.2575 ± 0.0086
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9264 ± 0.0019
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2896 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9653 ± 0.0022
Cross-validation details (10-fold Crossvalidation)