Run
550266

Run 550266

Task 14951 (Supervised Classification) eeg-eye-state Uploaded 08-04-2016 by Hugo Spee
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Flow

weka.LogitBoost_Bagging_REPTree(3)J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
weka.REPTree(15)_M2
weka.REPTree(15)_V0.001
weka.REPTree(15)_N100
weka.REPTree(15)_S1
weka.REPTree(15)_Ptrue
weka.REPTree(15)_L-1
weka.REPTree(15)_I0.0
weka.LogitBoost_Bagging_REPTree(3)_Qtrue
weka.LogitBoost_Bagging_REPTree(3)_L-1.7976931348623157E308
weka.LogitBoost_Bagging_REPTree(3)_H1.0
weka.LogitBoost_Bagging_REPTree(3)_Z3.0
weka.LogitBoost_Bagging_REPTree(3)_O1
weka.LogitBoost_Bagging_REPTree(3)_E1
weka.LogitBoost_Bagging_REPTree(3)_S1
weka.LogitBoost_Bagging_REPTree(3)_I25
weka.LogitBoost_Bagging_REPTree(3)_Wweka.classifiers.meta.Bagging
weka.Bagging_REPTree(21)_P100
weka.Bagging_REPTree(21)_S1
weka.Bagging_REPTree(21)_num-slots1
weka.Bagging_REPTree(21)_I25
weka.Bagging_REPTree(21)_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
0.9937
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9614
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.9219
Cross-validation details (10-fold Crossvalidation)
KB relative information score
13748.5499
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.041
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4948
Cross-validation details (10-fold Crossvalidation)
Number of instances
14980
Per class
Cross-validation details (10-fold Crossvalidation)
OS information
[Oracle Corporation, 1.8.0_51, amd64, Windows 8.1, 6.3]
Precision
0.9615
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9614
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9924
Cross-validation details (10-fold Crossvalidation)
Recall
0.9614
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.0828
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4974
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.1806
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.3632
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
1430.5592
UserCPU time millis
100390.625
Cross-validation details (10-fold Crossvalidation)
UserCPU time millis training
100390.625
Cross-validation details (10-fold Crossvalidation)