DEVELOPMENT... OpenML
Run
159315

Run 159315

Task 3693 (Supervised Classification) fri_c4_100_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)_I40
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
0.8183
Per class
F measure
0.76
Per class
Kappa
0.5183
KB relative information score
45.938
Mean absolute error
0.2727
Mean prior absolute error
0.4982
Number of instances
100
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.76
Per class
Predictive accuracy
0.76
Prior entropy
0.9975
Recall
0.76
Per class
Relative absolute error
0.5473
Root mean prior squared error
0.4991
Root mean squared error
0.4481
Root relative squared error
0.8978
SciMark benchmark
924.6116
UserCPU time millis
70
UserCPU time millis training
70