Run
10434999

Run 10434999

Task 9977 (Supervised Classification) nomao Uploaded 24-12-2019 by Peng YU
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Flow

sklearn.ensemble._weight_boosting.AdaBoostClassifier(base_estimator=bsplitz .DecisionStumpClassifierV3)(1)An AdaBoost classifier. An AdaBoost [1] classifier is a meta-estimator that begins by fitting a classifier on the original dataset and then fits additional copies of the classifier on the same dataset but where the weights of incorrectly classified instances are adjusted such that subsequent classifiers focus more on difficult cases. This class implements the algorithm known as AdaBoost-SAMME [2].
bsplitz.DecisionStumpClassifierV3(1)_default_feature_type"numerical"
bsplitz.DecisionStumpClassifierV3(1)_nominal_method"bsplitz"
bsplitz.DecisionStumpClassifierV3(1)_non_default_feature_colmns"6,7,14,15,22,23,30,31,38,39,46,47,54,55,62,63,70,71,78,79,86,87,91,95,99,103,107,111,115,118"
sklearn.ensemble._weight_boosting.AdaBoostClassifier(base_estimator=bsplitz.DecisionStumpClassifierV3)(1)_algorithm"SAMME.R"
sklearn.ensemble._weight_boosting.AdaBoostClassifier(base_estimator=bsplitz.DecisionStumpClassifierV3)(1)_learning_rate1.0
sklearn.ensemble._weight_boosting.AdaBoostClassifier(base_estimator=bsplitz.DecisionStumpClassifierV3)(1)_n_estimators50
sklearn.ensemble._weight_boosting.AdaBoostClassifier(base_estimator=bsplitz.DecisionStumpClassifierV3)(1)_random_state40791

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
0.932 ± 0.0026
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8217 ± 0.0396
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.5992 ± 0.0753
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.3095 ± 0.0126
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.273 ± 0.0051
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4081 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Weighted recall
0.8137 ± 0.0442
Cross-validation details (10-fold Crossvalidation)
Number of instances
34465
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.858 ± 0.022
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8137 ± 0.0442
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.863 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.6689 ± 0.0126
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4517 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.362 ± 0.0025
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.8015 ± 0.0057
Cross-validation details (10-fold Crossvalidation)
Unweighted recall
0.8413 ± 0.02
Cross-validation details (10-fold Crossvalidation)