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HINT and cross-validation

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HINT and cross-validation

Postby Guest » Thu Sep 22, 2005 14:48


I am trying to use Orange to repeat the experiments in Zupan et al. (1999) "Learning by discovering concept hierarchies" and to perform more experiments with my own data. I know the class HINT can be used to generate a hierarchy as a classifier (orngCI.HINT). But I haven't found a way to use this classifier with 10-ford cross validation method implemented in orngTest.crossValidation:

Code: Select all
>>> data = orange.ExampleTable("")
>>> rootH = orngCI.HINT(type="complexity", boundSize=3)
>>> results = orngTest.crossValidation([rootH], data, folds=10)
Traceback (most recent call last):
  File "<stdin>", line 1, in ?
  File "C:\Python23\lib\site-packages\orange\", line 160, in crossValidation
    return apply(testWithIndices, (learners, (examples, weight), indices, indicesrandseed, pps), argkw)
  File "C:\Python23\lib\site-packages\orange\", line 366, in testWithIndices
    cr = classifiers[cl](ex, orange.GetBoth)
orange.KernelException: 'orange.Domain': attribute 'e'' not found

Seems it doesn't recognize the new attributes constructed by HINT. One solution could be to do all the procedure manually and step by step, that is instead of using HINT, I use orngCI.FeatureByMinComplexity and then orngCI.addAttribute and so on. But I would like to know wheather there is any better sulution.

Thanks in advance

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