DEVELOPMENT... OpenML
Run
9636

Run 9636

Task 9 (Supervised Classification) autos Uploaded 22-05-2014 by Felicia West
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Flow

weka.LogitBoost_DecisionStump(1)J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
weka.LogitBoost_DecisionStump(1)_F0
weka.LogitBoost_DecisionStump(1)_H1.0
weka.LogitBoost_DecisionStump(1)_I160
weka.LogitBoost_DecisionStump(1)_L-1.7976931348623157E308
weka.LogitBoost_DecisionStump(1)_P100
weka.LogitBoost_DecisionStump(1)_R1
weka.LogitBoost_DecisionStump(1)_S1
weka.LogitBoost_DecisionStump(1)_Wweka.classifiers.trees.DecisionStump

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.

19 Evaluation measures

Area under ROC curve
0.9428
Per class
F measure
0.7955
Per class
Kappa
0.7332
KB relative information score
154.9093
Mean absolute error
0.0557
Mean prior absolute error
0.2209
Number of instances
205
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7986
Per class
Predictive accuracy
0.7951
Prior entropy
2.3268
Recall
0.7951
Per class
Relative absolute error
0.2522
Root mean prior squared error
0.3318
Root mean squared error
0.2242
Root relative squared error
0.6758
SciMark benchmark
910.0299[560.66883299690021015.2555353338006484.10363182779514908.95975824819551581.1619395961168]