Run
550257

Run 550257

Task 3487 (Supervised Classification) thyroid_sick Uploaded 08-04-2016 by Jan van Rijn
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  • study_15 study_20 weka weka_3.7.13
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Flow

weka.SMO_PolyKernel(11)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.PolyKernel(9)_E1.0
weka.PolyKernel(9)_C250007
weka.SMO_PolyKernel(11)_C1.0
weka.SMO_PolyKernel(11)_N0
weka.SMO_PolyKernel(11)_L0.001
weka.SMO_PolyKernel(11)_P1.0E-12
weka.SMO_PolyKernel(11)_V-1
weka.SMO_PolyKernel(11)_W1
weka.SMO_PolyKernel(11)_Kweka.classifiers.functions.supportVector.PolyKernel

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
0.5
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.9091
Per class
Cross-validation details (10-fold Crossvalidation)
KB relative information score
909.0798
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.0612
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.1152
Cross-validation details (10-fold Crossvalidation)
Number of instances
3772
Per class
Cross-validation details (10-fold Crossvalidation)
OS information
[Oracle Corporation, 1.8.0_77, amd64, Linux, 3.10.0-327.13.1.el7.x86_64]
Precision
0.8813
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9388
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.3333
Cross-validation details (10-fold Crossvalidation)
Recall
0.9388
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.5317
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.2398
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2475
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
1.0321
Cross-validation details (10-fold Crossvalidation)
SciMark benchmark
1001.246
UserCPU time millis
310
Cross-validation details (10-fold Crossvalidation)
UserCPU time millis testing
10
Cross-validation details (10-fold Crossvalidation)
UserCPU time millis training
300
Cross-validation details (10-fold Crossvalidation)