DEVELOPMENT... OpenML
Run
9235

Run 9235

Task 35 (Supervised Classification) dermatology Uploaded 22-05-2014 by Felicia West
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Flow

weka.LogitBoost_DecisionStump(1)J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
weka.LogitBoost_DecisionStump(1)_F0
weka.LogitBoost_DecisionStump(1)_H1.0
weka.LogitBoost_DecisionStump(1)_I160
weka.LogitBoost_DecisionStump(1)_L-1.7976931348623157E308
weka.LogitBoost_DecisionStump(1)_P100
weka.LogitBoost_DecisionStump(1)_R1
weka.LogitBoost_DecisionStump(1)_S1
weka.LogitBoost_DecisionStump(1)_Wweka.classifiers.trees.DecisionStump

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

19 Evaluation measures

Area under ROC curve
0.9863
Per class
F measure
0.9535
Per class
Kappa
0.9418
KB relative information score
345.4227
Mean absolute error
0.0149
Mean prior absolute error
0.2664
Number of instances
366
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9537
Per class
Predictive accuracy
0.9536
Prior entropy
2.4378
Recall
0.9536
Per class
Relative absolute error
0.056
Root mean prior squared error
0.3649
Root mean squared error
0.1181
Root relative squared error
0.3237
SciMark benchmark
947.5273[561.39059440769631015.5230404536866489.39918924322484912.43998791392861758.8835103978397]