DEVELOPMENT... OpenML
Run
160327

Run 160327

Task 5 (Supervised Classification) arrhythmia Uploaded 13-02-2015 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
0.7703
Per class
F measure
0.6034
Per class
Kappa
0.4011
KB relative information score
171.2896
Mean absolute error
0.051
Mean prior absolute error
0.0855
Number of instances
452
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.6273
Per class
Predictive accuracy
0.5885
Prior entropy
2.5222
Recall
0.5885
Per class
Relative absolute error
0.5957
Root mean prior squared error
0.2055
Root mean squared error
0.2195
Root relative squared error
1.068
SciMark benchmark
924.6116
UserCPU time millis
42460
UserCPU time millis training
42460