DEVELOPMENT... OpenML
Run
88890

Run 88890

Task 7293 (Supervised Classification) Click_prediction_small Uploaded 04-12-2014 by Robert Taylor
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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)_N3
weka.REPTree(5)_S1
weka.REPTree(5)_V0.001
weka.LogitBoost_REPTree(1)_P100
weka.LogitBoost_REPTree(1)_L-1.7976931348623157E308
weka.LogitBoost_REPTree(1)_H1.0
weka.LogitBoost_REPTree(1)_Z3.0
weka.LogitBoost_REPTree(1)_O1
weka.LogitBoost_REPTree(1)_E1
weka.LogitBoost_REPTree(1)_S1
weka.LogitBoost_REPTree(1)_I10
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
0.7073
Per class
Average cost
14.4241
Build CPU time
177.2303
Build memory
1325621181.9398
F measure
0.7914
Per class
Kappa
0.1662
KB relative information score
-389.9163
Mean absolute error
0.2432
Mean prior absolute error
0.2795
Number of instances
399482
Per class
OS information
[Oracle Corporation, 1.7.0_40, amd64, Windows 7, 6.1]
Precision
0.7857
Per class
Predictive accuracy
0.8282
Prior entropy
0.653
Recall
0.8282
Per class
Relative absolute error
0.87
Root mean prior squared error
0.3738
Root mean squared error
0.3628
Root relative squared error
0.9706
SciMark benchmark
1577.7377
Total cost
5762170