Run
10434862

Run 10434862

Task 53 (Supervised Classification) vehicle 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"18"
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_state35626

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
0.745 ± 0.0273
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.3918 ± 0.0629
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.1938 ± 0.0868
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.0855 ± 0.0325
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3589 ± 0.0062
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.3748 ± 0
Cross-validation details (10-fold Crossvalidation)
Weighted recall
0.3983 ± 0.0657
Cross-validation details (10-fold Crossvalidation)
Number of instances
846
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.441 ± 0.065
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.3983 ± 0.0657
Cross-validation details (10-fold Crossvalidation)
Prior entropy
1.9991 ± 0.0004
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9574 ± 0.0165
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4329 ± 0
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4178 ± 0.0051
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.965 ± 0.0116
Cross-validation details (10-fold Crossvalidation)
Unweighted recall
0.3935 ± 0.0662
Cross-validation details (10-fold Crossvalidation)