DEVELOPMENT... OpenML
Run
157804

Run 157804

Task 3481 (Supervised Classification) isolet 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
0.9978
Per class
F measure
0.9272
Per class
Kappa
0.9242
KB relative information score
7295.9457
Mean absolute error
0.0082
Mean prior absolute error
0.074
Number of instances
7797
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9274
Per class
Predictive accuracy
0.9272
Prior entropy
4.7004
Recall
0.9272
Per class
Relative absolute error
0.1111
Root mean prior squared error
0.1923
Root mean squared error
0.0652
Root relative squared error
0.3389
SciMark benchmark
902.4773
UserCPU time millis
826920
UserCPU time millis testing
60
UserCPU time millis training
826860