DEVELOPMENT... OpenML
Run
156936

Run 156936

Task 3599 (Supervised Classification) machine_cpu 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
0.9754
Per class
F measure
0.9284
Per class
Kappa
0.8181
KB relative information score
162.265
Mean absolute error
0.0827
Mean prior absolute error
0.3933
Number of instances
209
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9287
Per class
Predictive accuracy
0.9282
Prior entropy
0.8417
Recall
0.9282
Per class
Relative absolute error
0.2103
Root mean prior squared error
0.4429
Root mean squared error
0.2076
Root relative squared error
0.4687
SciMark benchmark
929.566
UserCPU time millis
10
UserCPU time millis training
10