Run
10560174

Run 10560174

Task 9957 (Supervised Classification) qsar-biodeg Uploaded 13-08-2021 by Sergey Redyuk
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Flow

sklearn.tree.tree.ExtraTreeClassifier(28)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.tree.ExtraTreeClassifier(28)_class_weightnull
sklearn.tree.tree.ExtraTreeClassifier(28)_criterion"gini"
sklearn.tree.tree.ExtraTreeClassifier(28)_max_depth1000
sklearn.tree.tree.ExtraTreeClassifier(28)_max_features"auto"
sklearn.tree.tree.ExtraTreeClassifier(28)_max_leaf_nodesnull
sklearn.tree.tree.ExtraTreeClassifier(28)_min_impurity_split1e-07
sklearn.tree.tree.ExtraTreeClassifier(28)_min_samples_leaf1
sklearn.tree.tree.ExtraTreeClassifier(28)_min_samples_split2
sklearn.tree.tree.ExtraTreeClassifier(28)_min_weight_fraction_leaf0.0
sklearn.tree.tree.ExtraTreeClassifier(28)_random_state60400
sklearn.tree.tree.ExtraTreeClassifier(28)_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
0.7871 ± 0.042
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.805 ± 0.0373
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.5669 ± 0.0822
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.5404 ± 0.0878
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1962 ± 0.0376
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4472 ± 0.0012
Cross-validation details (10-fold Crossvalidation)
Weighted recall
0.8038 ± 0.0376
Cross-validation details (10-fold Crossvalidation)
Number of instances
1055
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8067 ± 0.0373
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8038 ± 0.0376
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9223 ± 0.0036
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4387 ± 0.0839
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4728 ± 0.0013
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.443 ± 0.0423
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9368 ± 0.089
Cross-validation details (10-fold Crossvalidation)
Unweighted recall
0.7871 ± 0.042
Cross-validation details (10-fold Crossvalidation)