DEVELOPMENT... OpenML
Run
157197

Run 157197

Task 3856 (Supervised Classification) kdd_ipums_la_97-small Uploaded 11-02-2015 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)_I10
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
0.992
Per class
F measure
0.9773
Per class
Kappa
0.9516
KB relative information score
6460.2036
Mean absolute error
0.0412
Mean prior absolute error
0.466
Number of instances
7019
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9782
Per class
Predictive accuracy
0.9772
Prior entropy
0.9504
Recall
0.9772
Per class
Relative absolute error
0.0884
Root mean prior squared error
0.4827
Root mean squared error
0.1399
Root relative squared error
0.2898
SciMark benchmark
931.2336
UserCPU time millis
580
UserCPU time millis testing
10
UserCPU time millis training
570