DEVELOPMENT... OpenML
Run
158821

Run 158821

Task 6 (Supervised Classification) letter 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
0.9913
Per class
F measure
0.8375
Per class
Kappa
0.8308
KB relative information score
16671.8434
Mean absolute error
0.0215
Mean prior absolute error
0.074
Number of instances
20000
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8388
Per class
Predictive accuracy
0.8373
Prior entropy
4.6998
Recall
0.8373
Per class
Relative absolute error
0.2902
Root mean prior squared error
0.1923
Root mean squared error
0.0957
Root relative squared error
0.4975
SciMark benchmark
902.4773
UserCPU time millis
81970
UserCPU time millis testing
90
UserCPU time millis training
81880