DEVELOPMENT... OpenML
Run
157957

Run 157957

Task 3599 (Supervised Classification) machine_cpu 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
0.9713
Per class
F measure
0.9376
Per class
Kappa
0.8405
KB relative information score
166.6386
Mean absolute error
0.0747
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
0.9375
Per class
Predictive accuracy
0.9378
Prior entropy
0.8417
Recall
0.9378
Per class
Relative absolute error
0.1898
Root mean prior squared error
0.4429
Root mean squared error
0.2139
Root relative squared error
0.483
SciMark benchmark
947.9494
UserCPU time millis
10
UserCPU time millis training
10