Run
10432728

Run 10432728

Task 6 (Supervised Classification) letter 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_state53562
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
0.906 ± 0.0055
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8193 ± 0.0105
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.8119 ± 0.011
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.8169 ± 0.0107
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0139 ± 0.0008
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.074 ± 0
Cross-validation details (10-fold Crossvalidation)
Weighted recall
0.8192 ± 0.0106
Cross-validation details (10-fold Crossvalidation)
Number of instances
20000
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8195 ± 0.0105
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8192 ± 0.0106
Cross-validation details (10-fold Crossvalidation)
Prior entropy
4.6998 ± 0
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.1881 ± 0.011
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.1923 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1179 ± 0.0035
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.6133 ± 0.018
Cross-validation details (10-fold Crossvalidation)
Unweighted recall
0.8188 ± 0.0106
Cross-validation details (10-fold Crossvalidation)