Run
10434855

Run 10434855

Task 1 (Supervised Classification) anneal Uploaded 23-12-2019 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"0,1,2,5,6,7,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,35,36,37,38"
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_state6100

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.

15 Evaluation measures

Area under ROC curve
0.9438 ± 0.0209
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.054 ± 0.1389
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.4144 ± 0.0071
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0849 ± 0.0013
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1343 ± 0.0012
Cross-validation details (10-fold Crossvalidation)
Weighted recall
0.7695 ± 0.023
Cross-validation details (10-fold Crossvalidation)
Number of instances
898
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.7695 ± 0.023
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.1915 ± 0.0248
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.6318 ± 0.0062
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2582 ± 0.0024
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2211 ± 0.0018
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.8564 ± 0.0081
Cross-validation details (10-fold Crossvalidation)