Run
134706

Run 134706

Task 265 (Supervised Classification) dermatology Uploaded 28-12-2014 by Joaquin Vanschoren
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Flow

weka.AdaBoostM1_RandomTree(2)Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
weka.AdaBoostM1_RandomTree(2)_I20
weka.AdaBoostM1_RandomTree(2)_P100
weka.AdaBoostM1_RandomTree(2)_S1
weka.AdaBoostM1_RandomTree(2)_Wweka.classifiers.trees.RandomTree
weka.RandomTree(2)_K0
weka.RandomTree(2)_M1.0
weka.RandomTree(2)_S1
weka.RandomTree(2)_V0.001

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.

21 Evaluation measures

Area under ROC curve
0.9468
Per class
Cross-validation details (33% Holdout set)
Build CPU time
0.002
Cross-validation details (33% Holdout set)
Build memory
1021115640
Cross-validation details (33% Holdout set)
F measure
0.8995
Per class
Cross-validation details (33% Holdout set)
Kappa
0.873
Cross-validation details (33% Holdout set)
KB relative information score
103.897
Cross-validation details (33% Holdout set)
Mean absolute error
0.0341
Cross-validation details (33% Holdout set)
Mean prior absolute error
0.2653
Cross-validation details (33% Holdout set)
Number of instances
120
Per class
Cross-validation details (33% Holdout set)
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.902
Per class
Cross-validation details (33% Holdout set)
Predictive accuracy
0.9
Cross-validation details (33% Holdout set)
Prior entropy
2.4378
Cross-validation details (33% Holdout set)
Recall
0.9
Per class
Cross-validation details (33% Holdout set)
Relative absolute error
0.1284
Cross-validation details (33% Holdout set)
Root mean prior squared error
0.3633
Cross-validation details (33% Holdout set)
Root mean squared error
0.1777
Cross-validation details (33% Holdout set)
Root relative squared error
0.489
Cross-validation details (33% Holdout set)
SciMark benchmark
946.9091