DEVELOPMENT... OpenML
Run
157111

Run 157111

Task 3773 (Supervised Classification) fri_c1_1000_10 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
0.9389
Per class
F measure
0.8674
Per class
Kappa
0.7295
KB relative information score
558.9539
Mean absolute error
0.2347
Mean prior absolute error
0.4918
Number of instances
1000
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8683
Per class
Predictive accuracy
0.868
Prior entropy
0.9882
Recall
0.868
Per class
Relative absolute error
0.4773
Root mean prior squared error
0.4959
Root mean squared error
0.3169
Root relative squared error
0.6391
SciMark benchmark
929.566
UserCPU time millis
20
UserCPU time millis training
20