Run
506092

Run 506092

Task 57 (Supervised Classification) ionosphere Uploaded 16-01-2016 by Casey Davis
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Flow

weka.SMO_Puk(1)J. Platt: Fast Training of Support Vector Machines using Sequential Minimal Optimization. In B. Schoelkopf and C. Burges and A. Smola, editors, Advances in Kernel Methods - Support Vector Learning, 1998. S.S. Keerthi, S.K. Shevade, C. Bhattacharyya, K.R.K. Murthy (2001). Improvements to Platt's SMO Algorithm for SVM Classifier Design. Neural Computation. 13(3):637-649. Trevor Hastie, Robert Tibshirani: Classification by Pairwise Coupling. In: Advances in Neural Information Processing Systems, 1998.
weka.SMO_Puk(1)_C1.4966346405409632
weka.SMO_Puk(1)_N1
weka.SMO_Puk(1)_L0.001
weka.SMO_Puk(1)_P1.0E-12
weka.SMO_Puk(1)_Mtrue
weka.SMO_Puk(1)_V-1
weka.SMO_Puk(1)_W1
weka.SMO_Puk(1)_Kweka.classifiers.functions.supportVector.Puk
weka.Puk(5)_O0.4174335597767368
weka.Puk(5)_S3.471183917034118
weka.Puk(5)_C250007

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
0.9661
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9489
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.8893
Cross-validation details (10-fold Crossvalidation)
KB relative information score
305.1086
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0602
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4604
Cross-validation details (10-fold Crossvalidation)
Number of instances
351
Per class
Cross-validation details (10-fold Crossvalidation)
OS information
[Oracle Corporation, 1.8.0_60, amd64, Linux, 3.16.0-38-generic]
Precision
0.9493
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9487
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.9425
Cross-validation details (10-fold Crossvalidation)
Recall
0.9487
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.1307
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4797
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2018
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.4206
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
1247.3649
UserCPU time millis
90
Cross-validation details (10-fold Crossvalidation)
UserCPU time millis testing
20
Cross-validation details (10-fold Crossvalidation)
UserCPU time millis training
70
Cross-validation details (10-fold Crossvalidation)