DEVELOPMENT... OpenML
Run
158750

Run 158750

Task 7287 (Supervised Classification) adult Uploaded 12-02-2015 by Felicia West
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


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
0.9035
Per class
Average cost
0.0749
F measure
0.8412
Per class
Kappa
0.5449
KB relative information score
19729.4794
Mean absolute error
0.2092
Mean prior absolute error
0.3641
Number of instances
48842
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8429
Per class
Predictive accuracy
0.8502
Prior entropy
0.7939
Recall
0.8502
Per class
Relative absolute error
0.5745
Root mean prior squared error
0.4266
Root mean squared error
0.321
Root relative squared error
0.7524
SciMark benchmark
911.3823
Total cost
3658
UserCPU time millis
2410
UserCPU time millis testing
30
UserCPU time millis training
2380