DEVELOPMENT... OpenML
Run
157284

Run 157284

Task 3948 (Supervised Classification) KDDCup09_upselling 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
0.8554
Per class
F measure
0.9441
Per class
Kappa
0.5445
KB relative information score
9295.977
Mean absolute error
0.0915
Mean prior absolute error
0.1364
Number of instances
50000
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9459
Per class
Predictive accuracy
0.9509
Prior entropy
0.3794
Recall
0.9509
Per class
Relative absolute error
0.6707
Root mean prior squared error
0.2612
Root mean squared error
0.211
Root relative squared error
0.808
SciMark benchmark
931.2336
UserCPU time millis
35160
UserCPU time millis testing
70
UserCPU time millis training
35090