Run
101501

Run 101501

Task 289 (Supervised Classification) iris Uploaded 08-12-2014 by Joaquin Vanschoren
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Flow

weka.SMO_PolyKernel(6)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(4)_C250007
weka.PolyKernel(4)_E1.0
weka.SMO_PolyKernel(6)_C1.0
weka.SMO_PolyKernel(6)_Kweka.classifiers.functions.supportVector.PolyKernel
weka.SMO_PolyKernel(6)_L0.001
weka.SMO_PolyKernel(6)_N0
weka.SMO_PolyKernel(6)_P1.0E-12
weka.SMO_PolyKernel(6)_V-1
weka.SMO_PolyKernel(6)_W1

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.

21 Evaluation measures

Area under ROC curve
0.9734
Per class
Cross-validation details (33% Holdout set)
Build CPU time
0.027
Cross-validation details (33% Holdout set)
Build memory
717148424
Cross-validation details (33% Holdout set)
F measure
0.9592
Per class
Cross-validation details (33% Holdout set)
Kappa
0.9386
Cross-validation details (33% Holdout set)
KB relative information score
29.6537
Cross-validation details (33% Holdout set)
Mean absolute error
0.2313
Cross-validation details (33% Holdout set)
Mean prior absolute error
0.4444
Cross-validation details (33% Holdout set)
Number of instances
49
Per class
Cross-validation details (33% Holdout set)
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.9592
Per class
Cross-validation details (33% Holdout set)
Predictive accuracy
0.9592
Cross-validation details (33% Holdout set)
Prior entropy
1.585
Cross-validation details (33% Holdout set)
Recall
0.9592
Per class
Cross-validation details (33% Holdout set)
Relative absolute error
0.5204
Cross-validation details (33% Holdout set)
Root mean prior squared error
0.4714
Cross-validation details (33% Holdout set)
Root mean squared error
0.2883
Cross-validation details (33% Holdout set)
Root relative squared error
0.6117
Cross-validation details (33% Holdout set)
SciMark benchmark
945.4085