DEVELOPMENT... OpenML
Run
157344

Run 157344

Task 7293 (Supervised Classification) Click_prediction_small Uploaded 11-02-2015 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)_I10
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
0.6746
Per class
Average cost
16.1538
F measure
0.7688
Per class
Kappa
0.0549
KB relative information score
-19722.1228
Mean absolute error
0.2657
Mean prior absolute error
0.2795
Number of instances
399482
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7884
Per class
Predictive accuracy
0.8333
Prior entropy
0.653
Recall
0.8333
Per class
Relative absolute error
0.9507
Root mean prior squared error
0.3738
Root mean squared error
0.3632
Root relative squared error
0.9715
SciMark benchmark
940.2922
Total cost
6453140
UserCPU time millis
30340
UserCPU time millis testing
390
UserCPU time millis training
29950