DEVELOPMENT... OpenML
Run
160914

Run 160914

Task 3600 (Supervised Classification) ailerons Uploaded 15-02-2015 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)_I160
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
0.9528
Per class
F measure
0.8803
Per class
Kappa
0.7548
KB relative information score
9320.3398
Mean absolute error
0.1651
Mean prior absolute error
0.4884
Number of instances
13750
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8803
Per class
Predictive accuracy
0.8804
Prior entropy
0.9832
Recall
0.8804
Per class
Relative absolute error
0.3381
Root mean prior squared error
0.4942
Root mean squared error
0.2924
Root relative squared error
0.5916
SciMark benchmark
936.6206
UserCPU time millis
17830
UserCPU time millis testing
10
UserCPU time millis training
17820