DEVELOPMENT... OpenML
Run
158245

Run 158245

Task 3881 (Supervised Classification) ipums_la_99-small 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)_I20
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
0.902
Per class
F measure
0.9137
Per class
Kappa
0.132
KB relative information score
-2974.1146
Mean absolute error
0.0956
Mean prior absolute error
0.1203
Number of instances
8844
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9099
Per class
Predictive accuracy
0.9348
Prior entropy
0.3444
Recall
0.9348
Per class
Relative absolute error
0.7946
Root mean prior squared error
0.2452
Root mean squared error
0.22
Root relative squared error
0.8974
SciMark benchmark
932.3943
UserCPU time millis
1020
UserCPU time millis testing
10
UserCPU time millis training
1010