DEVELOPMENT... OpenML
Run
161115

Run 161115

Task 3799 (Supervised Classification) fri_c3_500_10 Uploaded 15-02-2015 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)_I160
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
0.9602
Per class
F measure
0.88
Per class
Kappa
0.7583
KB relative information score
366.0525
Mean absolute error
0.1357
Mean prior absolute error
0.4961
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
0.8801
Per class
Predictive accuracy
0.88
Prior entropy
0.9945
Recall
0.88
Per class
Relative absolute error
0.2736
Root mean prior squared error
0.4981
Root mean squared error
0.2906
Root relative squared error
0.5834
SciMark benchmark
936.6206
UserCPU time millis
190
UserCPU time millis training
190