Run
2244964

Run 2244964

Task 2068 (Supervised Classification) solar-flare Uploaded 18-05-2017 by Miguel Cachada
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Flow

weka.SMO_PolyKernel(15)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_PolyKernel(15)_C0.1
weka.SMO_PolyKernel(15)_N0
weka.SMO_PolyKernel(15)_L0.001
weka.SMO_PolyKernel(15)_P1.0E-12
weka.SMO_PolyKernel(15)_V-1
weka.SMO_PolyKernel(15)_W1
weka.SMO_PolyKernel(15)_Kweka.classifiers.functions.supportVector.PolyKernel
weka.SMO_PolyKernel(15)_calibratortrue
weka.PolyKernel(11)_E2.0
weka.PolyKernel(11)_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.

17 Evaluation measures

Area under ROC curve
0.4991
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.992
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
-0.0024
Cross-validation details (10-fold Crossvalidation)
KB relative information score
-95775.7185
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2239
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.0075
Cross-validation details (10-fold Crossvalidation)
Number of instances
1066
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.9906
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.9934
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.0626
Cross-validation details (10-fold Crossvalidation)
Recall
0.9934
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
30.0158
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.0558
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.2752
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
4.93
Cross-validation details (10-fold Crossvalidation)