DEVELOPMENT... OpenML
Run
160862

Run 160862

Task 3550 (Supervised Classification) analcatdata_asbestos Uploaded 15-02-2015 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)_I160
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
0.7644
Per class
F measure
0.7466
Per class
Kappa
0.4866
KB relative information score
34.2169
Mean absolute error
0.2948
Mean prior absolute error
0.4943
Number of instances
83
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7465
Per class
Predictive accuracy
0.747
Prior entropy
0.9919
Recall
0.747
Per class
Relative absolute error
0.5965
Root mean prior squared error
0.4971
Root mean squared error
0.4726
Root relative squared error
0.9508
SciMark benchmark
945.6434
UserCPU time millis
20
UserCPU time millis testing
10
UserCPU time millis training
10