DEVELOPMENT... OpenML
Run
157891

Run 157891

Task 3532 (Supervised Classification) tr12.wc 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
0.9844
Per class
F measure
0.884
Per class
Kappa
0.8612
KB relative information score
273.3996
Mean absolute error
0.0308
Mean prior absolute error
0.2079
Number of instances
313
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8835
Per class
Predictive accuracy
0.885
Prior entropy
2.7783
Recall
0.885
Per class
Relative absolute error
0.1483
Root mean prior squared error
0.3222
Root mean squared error
0.1465
Root relative squared error
0.4545
SciMark benchmark
902.4773
UserCPU time millis
260660
UserCPU time millis training
260660