DEVELOPMENT... OpenML
Run
157764

Run 157764

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)_I20
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
0.8837
Per class
F measure
0.8219
Per class
Kappa
0.4937
KB relative information score
12810.8781
Mean absolute error
0.2279
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
0.8205
Per class
Predictive accuracy
0.8301
Prior entropy
0.7951
Recall
0.8301
Per class
Relative absolute error
0.6247
Root mean prior squared error
0.4271
Root mean squared error
0.3379
Root relative squared error
0.7912
SciMark benchmark
934.5243
UserCPU time millis
97410
UserCPU time millis testing
30
UserCPU time millis training
97380