DEVELOPMENT... OpenML
Run
159077

Run 159077

Task 3494 (Supervised Classification) monks-problems-3 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)_I40
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
0.9849
Per class
F measure
0.9801
Per class
Kappa
0.9602
KB relative information score
506.1215
Mean absolute error
0.05
Mean prior absolute error
0.4992
Number of instances
554
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9802
Per class
Predictive accuracy
0.9801
Prior entropy
0.9989
Recall
0.9801
Per class
Relative absolute error
0.1002
Root mean prior squared error
0.4996
Root mean squared error
0.137
Root relative squared error
0.2741
SciMark benchmark
943.2817
UserCPU time millis
10
UserCPU time millis training
10