DEVELOPMENT... OpenML
Run
160123

Run 160123

Task 3771 (Supervised Classification) chscase_census3 Uploaded 13-02-2015 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)_I80
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
0.4065
Per class
F measure
0.4579
Per class
Kappa
-0.0856
KB relative information score
-30.3263
Mean absolute error
0.5318
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
0.4577
Per class
Predictive accuracy
0.46
Prior entropy
0.9989
Recall
0.46
Per class
Relative absolute error
1.0652
Root mean prior squared error
0.4996
Root mean squared error
0.5722
Root relative squared error
1.1454
SciMark benchmark
924.6116
UserCPU time millis
60
UserCPU time millis training
60