DEVELOPMENT... OpenML
Run
161086

Run 161086

Task 3771 (Supervised Classification) chscase_census3 Uploaded 15-02-2015 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)_I160
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
0.4082
Per class
F measure
0.4355
Per class
Kappa
-0.1307
KB relative information score
-35.0306
Mean absolute error
0.5383
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
0.4351
Per class
Predictive accuracy
0.4375
Prior entropy
0.9989
Recall
0.4375
Per class
Relative absolute error
1.0782
Root mean prior squared error
0.4996
Root mean squared error
0.5921
Root relative squared error
1.1852
SciMark benchmark
933.8635
UserCPU time millis
150
UserCPU time millis training
150