DEVELOPMENT... OpenML
Run
158295

Run 158295

Task 3536 (Supervised Classification) oh10.wc 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
0.9671
Per class
F measure
0.7946
Per class
Kappa
0.7676
KB relative information score
804.3336
Mean absolute error
0.0522
Mean prior absolute error
0.1768
Number of instances
1050
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.7966
Per class
Predictive accuracy
0.7952
Prior entropy
3.2054
Recall
0.7952
Per class
Relative absolute error
0.2952
Root mean prior squared error
0.2973
Root mean squared error
0.169
Root relative squared error
0.5687
SciMark benchmark
934.5243
UserCPU time millis
532470
UserCPU time millis training
532470