Run
10457062

Run 10457062

Task 211993 (Supervised Regression) titanic_2 Uploaded 19-05-2020 by sri ranga sai
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  • openml-python Sklearn_0.22.2.post1.
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Flow

sklearn.tree._classes.ExtraTreeClassifier(2)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(2)_ccp_alpha0.0
sklearn.tree._classes.ExtraTreeClassifier(2)_class_weightnull
sklearn.tree._classes.ExtraTreeClassifier(2)_criterion"gini"
sklearn.tree._classes.ExtraTreeClassifier(2)_max_depthnull
sklearn.tree._classes.ExtraTreeClassifier(2)_max_features"auto"
sklearn.tree._classes.ExtraTreeClassifier(2)_max_leaf_nodesnull
sklearn.tree._classes.ExtraTreeClassifier(2)_min_impurity_decrease0.0
sklearn.tree._classes.ExtraTreeClassifier(2)_min_impurity_splitnull
sklearn.tree._classes.ExtraTreeClassifier(2)_min_samples_leaf1
sklearn.tree._classes.ExtraTreeClassifier(2)_min_samples_split2
sklearn.tree._classes.ExtraTreeClassifier(2)_min_weight_fraction_leaf0.0
sklearn.tree._classes.ExtraTreeClassifier(2)_random_state33068
sklearn.tree._classes.ExtraTreeClassifier(2)_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.

7 Evaluation measures

Mean absolute error
0.202 ± 0.0457
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.473 ± 0.0124
Cross-validation details (10-fold Crossvalidation)
Number of instances
891
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4271 ± 0.0992
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4863 ± 0.0129
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4495 ± 0.0534
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9242 ± 0.1143
Cross-validation details (10-fold Crossvalidation)