Run
25560

Run 25560

Task 83 (Learning Curve) mushroom Uploaded 19-08-2014 by Jan van Rijn
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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
1
Per class
Build CPU time
0.3823
Build memory
4768422281.9413
F measure
1
Per class
Kappa
1
KB relative information score
1 ± 0
Mean prior absolute error
0.4994 ± 0
Number of instances
81240
Per class
OS information
[Oracle Corporation, 1.7.0_55, amd64, Linux, 3.8.0-44-generic]
Precision
1
Per class
Predictive accuracy
1
Prior entropy
0.9991 ± 0
Recall
1
Per class
Root mean prior squared error
0.4997 ± 0
SciMark benchmark
1120.4498[657.4596922373555983.6421727629752545.0466032518232946.02673641693762470.073911414107]