Run
8886083

Run 8886083

Task 167133 (Supervised Classification) CIFAR_10_small Uploaded 16-03-2018 by jiawen wang
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

sklearn.pipeline.Pipeline(preprocessing=sklearn.preprocessing.data.MinMaxSc aler,feature=sklearn.feature_selection.univariate_selection.SelectKBest,cla ssifier=sklearn.ensemble.forest.RandomForestClassifier)(1)Automatically created scikit-learn flow.
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_state19120
sklearn.ensemble.forest.RandomForestClassifier(32)_verbose0
sklearn.ensemble.forest.RandomForestClassifier(32)_warm_startfalse
sklearn.preprocessing.data.MinMaxScaler(3)_copytrue
sklearn.preprocessing.data.MinMaxScaler(3)_feature_range[0, 1]
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.chi2"}
sklearn.pipeline.Pipeline(preprocessing=sklearn.preprocessing.data.MinMaxScaler,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
0.7155 ± 0.008
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.25 ± 0.0067
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.1729 ± 0.0076
Cross-validation details (10-fold Crossvalidation)
KB relative information score
3797.5794 ± 7.1397
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.167 ± 0.0004
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
0.2519 ± 0.0074
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.2557 ± 0.0068
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3218
Cross-validation details (10-fold Crossvalidation)
Recall
0.2557 ± 0.0068
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9278 ± 0.0021
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2898 ± 0.0007
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.966 ± 0.0023
Cross-validation details (10-fold Crossvalidation)