DEVELOPMENT... OpenML
Run
158126

Run 158126

Task 3763 (Supervised Classification) chscase_census6 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
0.4371
Per class
F measure
0.4576
Per class
Kappa
-0.1189
KB relative information score
-21.2957
Mean absolute error
0.5033
Mean prior absolute error
0.4848
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
0.449
Per class
Predictive accuracy
0.49
Prior entropy
0.978
Recall
0.49
Per class
Relative absolute error
1.0382
Root mean prior squared error
0.4923
Root mean squared error
0.5309
Root relative squared error
1.0784
SciMark benchmark
947.9494
UserCPU time millis
20
UserCPU time millis training
20