Run
10434860

Run 10434860

Task 12 (Supervised Classification) mfeat-factors 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"216"
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_state29259

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
0.7347 ± 0.0837
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.503 ± 0.0332
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.4556 ± 0.1823
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.0914 ± 0.0455
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1745 ± 0.0031
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.18
Cross-validation details (10-fold Crossvalidation)
Weighted recall
0.51 ± 0.1641
Cross-validation details (10-fold Crossvalidation)
Number of instances
2000
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.5554 ± 0.0245
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.51 ± 0.1641
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.3219
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9697 ± 0.0174
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2924 ± 0.0043
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9747 ± 0.0142
Cross-validation details (10-fold Crossvalidation)
Unweighted recall
0.51 ± 0.1641
Cross-validation details (10-fold Crossvalidation)