DEVELOPMENT... OpenML
Run
157122

Run 157122

Task 3784 (Supervised Classification) analcatdata_seropositive 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
0.9682
Per class
F measure
0.9618
Per class
Kappa
0.9153
KB relative information score
107.6131
Mean absolute error
0.0929
Mean prior absolute error
0.4548
Number of instances
132
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9626
Per class
Predictive accuracy
0.9621
Prior entropy
0.9347
Recall
0.9621
Per class
Relative absolute error
0.2043
Root mean prior squared error
0.4765
Root mean squared error
0.2025
Root relative squared error
0.4249
SciMark benchmark
931.2336