DEVELOPMENT... OpenML
Run
159038

Run 159038

Task 2074 (Supervised Classification) satimage 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)_I40
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
0.9857
Per class
F measure
0.8873
Per class
Kappa
0.8623
KB relative information score
5481.9132
Mean absolute error
0.0519
Mean prior absolute error
0.2701
Number of instances
6430
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8867
Per class
Predictive accuracy
0.8886
Prior entropy
2.4836
Recall
0.8886
Per class
Relative absolute error
0.1923
Root mean prior squared error
0.3675
Root mean squared error
0.165
Root relative squared error
0.449
SciMark benchmark
924.6116
UserCPU time millis
9530
UserCPU time millis testing
10
UserCPU time millis training
9520