DEVELOPMENT... OpenML
Run
157254

Run 157254

Task 3916 (Supervised Classification) kc1-binary 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
0.7544
Per class
F measure
0.6754
Per class
Kappa
0.3302
KB relative information score
42.3324
Mean absolute error
0.343
Mean prior absolute error
0.4853
Number of instances
145
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.6751
Per class
Predictive accuracy
0.6759
Prior entropy
0.979
Recall
0.6759
Per class
Relative absolute error
0.7067
Root mean prior squared error
0.4925
Root mean squared error
0.4704
Root relative squared error
0.9551
SciMark benchmark
943.2817
UserCPU time millis
20
UserCPU time millis training
20