DEVELOPMENT... OpenML
Run
159380

Run 159380

Task 3771 (Supervised Classification) chscase_census3 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
0.4329
Per class
F measure
0.4691
Per class
Kappa
-0.0638
KB relative information score
-20.7985
Mean absolute error
0.5222
Mean prior absolute error
0.4992
Number of instances
400
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.4689
Per class
Predictive accuracy
0.47
Prior entropy
0.9989
Recall
0.47
Per class
Relative absolute error
1.046
Root mean prior squared error
0.4996
Root mean squared error
0.5536
Root relative squared error
1.1081
SciMark benchmark
924.6116
UserCPU time millis
30
UserCPU time millis training
30

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