DEVELOPMENT... OpenML
Run
89028

Run 89028

Task 7293 (Supervised Classification) Click_prediction_small Uploaded 06-12-2014 by Cook
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Flow

weka.LogitBoost_REPTree(1)J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
weka.REPTree(5)_I0.0
weka.REPTree(5)_L-1
weka.REPTree(5)_M2
weka.REPTree(5)_N2
weka.REPTree(5)_S1
weka.REPTree(5)_V0.001
weka.LogitBoost_REPTree(1)_P90
weka.LogitBoost_REPTree(1)_L-1.7976931348623157E308
weka.LogitBoost_REPTree(1)_H0.0
weka.LogitBoost_REPTree(1)_Z3.0
weka.LogitBoost_REPTree(1)_O4
weka.LogitBoost_REPTree(1)_E4
weka.LogitBoost_REPTree(1)_S1
weka.LogitBoost_REPTree(1)_I2
weka.LogitBoost_REPTree(1)_Wweka.classifiers.trees.REPTree

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.

21 Evaluation measures

Area under ROC curve
0.5
Per class
Average cost
16.794
Build CPU time
16.7021
Build memory
1256689271.2038
F measure
0.7558
Per class
KB relative information score
-639504.4331
Mean absolute error
0.5
Mean prior absolute error
0.2795
Number of instances
399482
Per class
OS information
[Oracle Corporation, 1.8.0_25, amd64, Windows 8.1, 6.3]
Precision
0.6923
Per class
Predictive accuracy
0.8321
Prior entropy
0.653
Recall
0.8321
Per class
Relative absolute error
1.7891
Root mean prior squared error
0.3738
Root mean squared error
0.5
Root relative squared error
1.3376
SciMark benchmark
1444.1151
Total cost
6708900