DEVELOPMENT... OpenML
Run
157940

Run 157940

Task 3583 (Supervised Classification) rmftsa_ladata 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
0.9492
Per class
F measure
0.8836
Per class
Kappa
0.7629
KB relative information score
353.0244
Mean absolute error
0.1578
Mean prior absolute error
0.4921
Number of instances
508
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8838
Per class
Predictive accuracy
0.8839
Prior entropy
0.9886
Recall
0.8839
Per class
Relative absolute error
0.3207
Root mean prior squared error
0.496
Root mean squared error
0.2966
Root relative squared error
0.598
SciMark benchmark
947.9494
UserCPU time millis
30
UserCPU time millis training
30