Run
258212

Run 258212

Task 3550 (Supervised Classification) analcatdata_asbestos Uploaded 05-03-2015 by Joaquin Vanschoren
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Flow

weka.RandomSubSpace_REPTree(4)Tin Kam Ho (1998). The Random Subspace Method for Constructing Decision Forests. IEEE Transactions on Pattern Analysis and Machine Intelligence. 20(8):832-844. URL http://citeseer.ist.psu.edu/ho98random.html.
weka.REPTree(9)_M2
weka.REPTree(9)_V0.001
weka.REPTree(9)_N3
weka.REPTree(9)_S1
weka.REPTree(9)_L-1
weka.REPTree(9)_I0.0
weka.RandomSubSpace_REPTree(4)_P0.5
weka.RandomSubSpace_REPTree(4)_S1
weka.RandomSubSpace_REPTree(4)_num-slots1
weka.RandomSubSpace_REPTree(4)_I80
weka.RandomSubSpace_REPTree(4)_Wweka.classifiers.trees.REPTree

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
0.8273
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.7477
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.492
Cross-validation details (10-fold Crossvalidation)
KB relative information score
28.1672
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.3447
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4943
Cross-validation details (10-fold Crossvalidation)
Number of instances
83
Per class
Cross-validation details (10-fold Crossvalidation)
OS information
[Oracle Corporation, 1.7.0_75, amd64, Linux, 3.16.0-29-generic]
Precision
0.7503
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.747
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9919
Cross-validation details (10-fold Crossvalidation)
Recall
0.747
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.6974
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4971
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.4061
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.817
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
898.1296
UserCPU time millis
10
Cross-validation details (10-fold Crossvalidation)
UserCPU time millis training
10
Cross-validation details (10-fold Crossvalidation)