DEVELOPMENT... OpenML
Run
159097

Run 159097

Task 3504 (Supervised Classification) webdata_wXa Uploaded 12-02-2015 by Felicia West
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Flow

weka.LogitBoost_DecisionStump(2)J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
weka.LogitBoost_DecisionStump(2)_E1
weka.LogitBoost_DecisionStump(2)_H1.0
weka.LogitBoost_DecisionStump(2)_I40
weka.LogitBoost_DecisionStump(2)_L-1.7976931348623157E308
weka.LogitBoost_DecisionStump(2)_O1
weka.LogitBoost_DecisionStump(2)_P100
weka.LogitBoost_DecisionStump(2)_S1
weka.LogitBoost_DecisionStump(2)_Wweka.classifiers.trees.DecisionStump
weka.LogitBoost_DecisionStump(2)_Z3.0

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

model
Model readable

A human-readable description of the model that was built.

model
Model serialized

A serialized description of the model that can be read by the tool that generated it.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

22 Evaluation measures

Area under ROC curve
0.8897
Per class
F measure
0.8273
Per class
Kappa
0.511
KB relative information score
13402.0142
Mean absolute error
0.2224
Mean prior absolute error
0.3648
Number of instances
36974
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8258
Per class
Predictive accuracy
0.8343
Prior entropy
0.7951
Recall
0.8343
Per class
Relative absolute error
0.6097
Root mean prior squared error
0.4271
Root mean squared error
0.3337
Root relative squared error
0.7814
SciMark benchmark
943.2817
UserCPU time millis
186990
UserCPU time millis testing
40
UserCPU time millis training
186950