DEVELOPMENT... OpenML
Run
159130

Run 159130

Task 3523 (Supervised Classification) tr23.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)_I40
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
0.99
Per class
F measure
0.9753
Per class
Kappa
0.9655
KB relative information score
192.79
Mean absolute error
0.01
Mean prior absolute error
0.2385
Number of instances
204
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9765
Per class
Predictive accuracy
0.9755
Prior entropy
2.1253
Recall
0.9755
Per class
Relative absolute error
0.042
Root mean prior squared error
0.3445
Root mean squared error
0.0886
Root relative squared error
0.2573
SciMark benchmark
938.2848
UserCPU time millis
260610
UserCPU time millis training
260610