DEVELOPMENT... OpenML
Run
158316

Run 158316

Task 2256 (Supervised Classification) BNG(pendigits) Uploaded 12-02-2015 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)_I20
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
0.9814
Per class
F measure
0.8312
Per class
Kappa
0.8128
KB relative information score
802152.5125
Mean absolute error
0.0527
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
0.8311
Per class
Predictive accuracy
0.8316
Prior entropy
3.3207
Recall
0.8316
Per class
Relative absolute error
0.2928
Root mean prior squared error
0.3
Root mean squared error
0.1559
Root relative squared error
0.5199
SciMark benchmark
931.2336
UserCPU time millis
2510830
UserCPU time millis testing
2050
UserCPU time millis training
2508780