DEVELOPMENT... OpenML
Run
159908

Run 159908

Task 3522 (Supervised Classification) tr11.wc Uploaded 13-02-2015 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)_I80
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
0.9866
Per class
F measure
0.9172
Per class
Kappa
0.9014
KB relative information score
366.4579
Mean absolute error
0.0173
Mean prior absolute error
0.1808
Number of instances
414
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9162
Per class
Predictive accuracy
0.9203
Prior entropy
2.7236
Recall
0.9203
Per class
Relative absolute error
0.0954
Root mean prior squared error
0.3004
Root mean squared error
0.1248
Root relative squared error
0.4154
SciMark benchmark
943.2817
UserCPU time millis
1718110
UserCPU time millis training
1718110