DEVELOPMENT... OpenML
Run
159687

Run 159687

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)_I80
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
0.891
Per class
F measure
0.8297
Per class
Kappa
0.5191
KB relative information score
13638.4674
Mean absolute error
0.22
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
0.8279
Per class
Predictive accuracy
0.8359
Prior entropy
0.7951
Recall
0.8359
Per class
Relative absolute error
0.603
Root mean prior squared error
0.4271
Root mean squared error
0.3327
Root relative squared error
0.7791
SciMark benchmark
945.6434
UserCPU time millis
344450
UserCPU time millis testing
40
UserCPU time millis training
344410