DEVELOPMENT... OpenML
Run
157243

Run 157243

Task 3905 (Supervised Classification) mc2 Uploaded 11-02-2015 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)_I10
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
0.5929
Per class
F measure
0.6583
Per class
Kappa
0.1924
KB relative information score
14.4422
Mean absolute error
0.3858
Mean prior absolute error
0.4381
Number of instances
161
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.6617
Per class
Predictive accuracy
0.6894
Prior entropy
0.9099
Recall
0.6894
Per class
Relative absolute error
0.8807
Root mean prior squared error
0.4676
Root mean squared error
0.4835
Root relative squared error
1.0339
SciMark benchmark
943.2817
UserCPU time millis
10
UserCPU time millis training
10

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