DEVELOPMENT... OpenML
Run
159172

Run 159172

Task 3522 (Supervised Classification) tr11.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
0.9893
Per class
F measure
0.9225
Per class
Kappa
0.9074
KB relative information score
369.2175
Mean absolute error
0.018
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
0.9227
Per class
Predictive accuracy
0.9251
Prior entropy
2.7236
Recall
0.9251
Per class
Relative absolute error
0.0994
Root mean prior squared error
0.3004
Root mean squared error
0.1182
Root relative squared error
0.3936
SciMark benchmark
911.3823
UserCPU time millis
926370
UserCPU time millis testing
10
UserCPU time millis training
926360