DEVELOPMENT... OpenML
Run
158263

Run 158263

Task 3896 (Supervised Classification) ada_agnostic 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
0.8951
Per class
F measure
0.8401
Per class
Kappa
0.5555
KB relative information score
1873.9475
Mean absolute error
0.2125
Mean prior absolute error
0.3732
Number of instances
4562
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8408
Per class
Predictive accuracy
0.8477
Prior entropy
0.8085
Recall
0.8477
Per class
Relative absolute error
0.5694
Root mean prior squared error
0.4319
Root mean squared error
0.3269
Root relative squared error
0.7569
SciMark benchmark
945.6434
UserCPU time millis
900
UserCPU time millis testing
10
UserCPU time millis training
890