DEVELOPMENT... OpenML
Run
159189

Run 159189

Task 3544 (Supervised Classification) analcatdata_broadwaymult 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
0.7759
Per class
F measure
0.5055
Per class
Kappa
0.351
KB relative information score
101.4792
Mean absolute error
0.1562
Mean prior absolute error
0.2203
Number of instances
285
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.5116
Per class
Predictive accuracy
0.5193
Prior entropy
2.4897
Recall
0.5193
Per class
Relative absolute error
0.7092
Root mean prior squared error
0.3314
Root mean squared error
0.3149
Root relative squared error
0.9501
SciMark benchmark
924.6116
UserCPU time millis
70
UserCPU time millis training
70

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