Run
10432750

Run 10432750

Task 11 (Supervised Classification) balance-scale Uploaded 13-12-2019 by Evan Peterson
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Flow

sklearn.tree._classes.ExtraTreeClassifier(1)An extremely randomized tree classifier. Extra-trees differ from classic decision trees in the way they are built. When looking for the best split to separate the samples of a node into two groups, random splits are drawn for each of the `max_features` randomly selected features and the best split among those is chosen. When `max_features` is set 1, this amounts to building a totally random decision tree. Warning: Extra-trees should only be used within ensemble methods.
sklearn.tree._classes.ExtraTreeClassifier(1)_ccp_alpha0.0
sklearn.tree._classes.ExtraTreeClassifier(1)_class_weightnull
sklearn.tree._classes.ExtraTreeClassifier(1)_criterion"gini"
sklearn.tree._classes.ExtraTreeClassifier(1)_max_depthnull
sklearn.tree._classes.ExtraTreeClassifier(1)_max_features"auto"
sklearn.tree._classes.ExtraTreeClassifier(1)_max_leaf_nodesnull
sklearn.tree._classes.ExtraTreeClassifier(1)_min_impurity_decrease0.0
sklearn.tree._classes.ExtraTreeClassifier(1)_min_impurity_splitnull
sklearn.tree._classes.ExtraTreeClassifier(1)_min_samples_leaf1
sklearn.tree._classes.ExtraTreeClassifier(1)_min_samples_split2
sklearn.tree._classes.ExtraTreeClassifier(1)_min_weight_fraction_leaf0.0
sklearn.tree._classes.ExtraTreeClassifier(1)_random_state36634
sklearn.tree._classes.ExtraTreeClassifier(1)_splitter"random"

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.

18 Evaluation measures

Area under ROC curve
0.8591 ± 0.0301
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8151 ± 0.0324
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.6824 ± 0.0733
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.6221 ± 0.0709
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1195 ± 0.0309
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.3798 ± 0.0012
Cross-validation details (10-fold Crossvalidation)
Weighted recall
0.8208 ± 0.0463
Cross-validation details (10-fold Crossvalidation)
Number of instances
625
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8095 ± 0.0215
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8208 ± 0.0463
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.3181 ± 0.0124
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.3146 ± 0.0811
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4356 ± 0.0014
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3456 ± 0.0433
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.7935 ± 0.099
Cross-validation details (10-fold Crossvalidation)
Unweighted recall
0.5938 ± 0.0333
Cross-validation details (10-fold Crossvalidation)