Package PyML :: Package classifiers :: Module lazyclass
[frames] | no frames]

Source Code for Module PyML.classifiers.lazyclass

 1   
 2  import os 
 3   
 4  import datafunc 
 5  import svm 
 6  import preproc 
 7  import composite 
 8  import modelSelection 
 9  import ker 
10   
11 -def rescale(Clist = [0.1, 1, 10, 100], data = None, **args) :
12 13 chain = composite.Chain([preproc.Rescale(), svm.SVM(**args)]) 14 if Clist is not None : 15 param = modelSelection.Param(chain, 'classifier.C', Clist) 16 return modelSelection.ModelSelector(param) 17 else : 18 return chain
19
20 -def rescaleGaussian(gammaList = [0.01, 0.05, 0.1, 0.3, 1, 2], data = None, **args) :
21 22 k = ker.Gaussian() 23 s=svm.SVM(k) 24 chain = composite.Chain([preproc.Rescale(), s]) 25 if gammaList is not None : 26 param = modelSelection.Param(chain, 27 'classifier.kernel.gamma', gammaList) 28 return modelSelection.ModelSelector(param) 29 else : 30 return chain
31
32 -def gaussianSelect(gammaList = [0.01, 0.05, 0.1, 0.3, 1, 2], **args) :
33 34 measure = 'balancedSuccessRate' 35 if 'measure' in args : 36 measure = args['measure'] 37 k = ker.Gaussian() 38 param = modelSelection.Param(svm.SVM(k), 39 'kernel.gamma', gammaList) 40 return modelSelection.ModelSelector(param, measure = measure)
41 42
43 -def RF(data = None, **args) :
44 45 from PyCode.PyML import randomForests2 46 rf = randomForests2.RF() 47 48 return rf
49