DEVELOPMENT... OpenML
Run
158030

Run 158030

Task 3670 (Supervised Classification) fri_c4_500_50 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)_I20
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
0.9237
Per class
F measure
0.844
Per class
Kappa
0.6869
KB relative information score
278.4472
Mean absolute error
0.2351
Mean prior absolute error
0.4984
Number of instances
500
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.844
Per class
Predictive accuracy
0.844
Prior entropy
0.9978
Recall
0.844
Per class
Relative absolute error
0.4717
Root mean prior squared error
0.4992
Root mean squared error
0.3328
Root relative squared error
0.6666
SciMark benchmark
947.9494
UserCPU time millis
110
UserCPU time millis training
110