DEVELOPMENT... OpenML
Run
157733

Run 157733

Task 3499 (Supervised Classification) squash-stored 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
0.7714
Per class
F measure
0.6732
Per class
Kappa
0.461
KB relative information score
24.4164
Mean absolute error
0.2381
Mean prior absolute error
0.4135
Number of instances
52
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.679
Per class
Predictive accuracy
0.6731
Prior entropy
1.4782
Recall
0.6731
Per class
Relative absolute error
0.5758
Root mean prior squared error
0.4538
Root mean squared error
0.4301
Root relative squared error
0.9478
SciMark benchmark
910.8389
UserCPU time millis
10
UserCPU time millis training
10