DEVELOPMENT... OpenML
Run
156910

Run 156910

Task 2256 (Supervised Classification) BNG(pendigits) 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
0.9743
Per class
F measure
0.8031
Per class
Kappa
0.7825
KB relative information score
758138.2343
Mean absolute error
0.0639
Mean prior absolute error
0.18
Number of instances
1000000
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8031
Per class
Predictive accuracy
0.8043
Prior entropy
3.3207
Recall
0.8043
Per class
Relative absolute error
0.3552
Root mean prior squared error
0.3
Root mean squared error
0.1693
Root relative squared error
0.5644
SciMark benchmark
929.566
UserCPU time millis
1347270
UserCPU time millis testing
2160
UserCPU time millis training
1345110