Run
10432744

Run 10432744

Task 6 (Supervised Classification) letter Uploaded 13-12-2019 by Evan Peterson
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


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_state63618
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
0.909 ± 0.0033
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8253 ± 0.0063
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.818 ± 0.0065
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.8229 ± 0.0063
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0135 ± 0.0005
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.074 ± 0
Cross-validation details (10-fold Crossvalidation)
Weighted recall
0.8251 ± 0.0063
Cross-validation details (10-fold Crossvalidation)
Number of instances
20000
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8258 ± 0.0066
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8251 ± 0.0063
Cross-validation details (10-fold Crossvalidation)
Prior entropy
4.6998 ± 0
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.182 ± 0.0065
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.1923 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.116 ± 0.0021
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.6032 ± 0.0108
Cross-validation details (10-fold Crossvalidation)
Unweighted recall
0.8248 ± 0.0062
Cross-validation details (10-fold Crossvalidation)