DEVELOPMENT... OpenML
Run
157966

Run 157966

Task 3608 (Supervised Classification) fri_c4_500_100 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
0.9257
Per class
F measure
0.8478
Per class
Kappa
0.6899
KB relative information score
283.5152
Mean absolute error
0.2255
Mean prior absolute error
0.4913
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
0.8478
Per class
Predictive accuracy
0.848
Prior entropy
0.9875
Recall
0.848
Per class
Relative absolute error
0.4589
Root mean prior squared error
0.4956
Root mean squared error
0.3277
Root relative squared error
0.6611
SciMark benchmark
947.9494
UserCPU time millis
210
UserCPU time millis training
210