OpenML
2157

Run 2157

Task 403 (Supervised Classification) eeg-eye-state Uploaded 12-01-2024 by Test Test
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Flow

sklearn.tree._classes.DecisionTreeClassifier(1)A decision tree classifier.
sklearn.tree._classes.DecisionTreeClassifier(1)_ccp_alpha0.0
sklearn.tree._classes.DecisionTreeClassifier(1)_class_weightnull
sklearn.tree._classes.DecisionTreeClassifier(1)_criterion"gini"
sklearn.tree._classes.DecisionTreeClassifier(1)_max_depthnull
sklearn.tree._classes.DecisionTreeClassifier(1)_max_featuresnull
sklearn.tree._classes.DecisionTreeClassifier(1)_max_leaf_nodesnull
sklearn.tree._classes.DecisionTreeClassifier(1)_min_impurity_decrease0.0
sklearn.tree._classes.DecisionTreeClassifier(1)_min_samples_leaf1
sklearn.tree._classes.DecisionTreeClassifier(1)_min_samples_split2
sklearn.tree._classes.DecisionTreeClassifier(1)_min_weight_fraction_leaf0.0
` for details">sklearn.tree._classes.DecisionTreeClassifier(1)_random_state10534
sklearn.tree._classes.DecisionTreeClassifier(1)_splitter"best"

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
0.8414 ± 0.0135
Per class
F measure
0.8434 ± 0.013
Per class
Kappa
0.6834 ± 0.0265
KB relative information score
0.6821 ± 0.0263
Mean absolute error
0.1565 ± 0.013
Mean prior absolute error
0.4948 ± 0
Weighted recall
0.8435 ± 0.013
Number of instances
14980
Per class
Precision
0.8434 ± 0.0131
Per class
Predictive accuracy
0.8435 ± 0.013
Prior entropy
0.9924 ± 0.0001
Relative absolute error
0.3164 ± 0.0262
Root mean prior squared error
0.4974 ± 0
Root mean squared error
0.3957 ± 0.0161
Root relative squared error
0.7955 ± 0.0323
Unweighted recall
0.8414 ± 0.0135