Run
10435000

Run 10435000

Task 9981 (Supervised Classification) cnae-9 Uploaded 24-12-2019 by Peng YU
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


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"856"
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_state60289

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
0.8325 ± 0.1254
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.5495 ± 0.0376
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.4865 ± 0.2787
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.156 ± 0.1196
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1839 ± 0.012
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1975
Cross-validation details (10-fold Crossvalidation)
Weighted recall
0.5435 ± 0.2478
Cross-validation details (10-fold Crossvalidation)
Number of instances
1080
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.6919 ± 0.0119
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.5435 ± 0.2478
Cross-validation details (10-fold Crossvalidation)
Prior entropy
3.1699
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.9309 ± 0.0605
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3143
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2951 ± 0.0169
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9389 ± 0.0537
Cross-validation details (10-fold Crossvalidation)
Unweighted recall
0.5435 ± 0.2478
Cross-validation details (10-fold Crossvalidation)