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| [6866] | 1 | # Description: Learn decision tree from data and output class probabilities for first few instances |
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| 2 | # Category: modelling |
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| 3 | # Uses: voting.tab |
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| 4 | # Classes: orngTree.TreeLearner |
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| 5 | # Referenced: c_otherclass.htm |
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| 6 | |
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| 7 | import orange, orngTree |
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| 8 | data = orange.ExampleTable("voting") |
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| 9 | |
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| 10 | tree = orngTree.TreeLearner(data, sameMajorityPruning=1, mForPruning=2) |
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| 11 | print "Possible classes:", data.domain.classVar.values |
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| 12 | print "Probabilities for democrats:" |
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| 13 | for i in range(5): |
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| 14 | p = tree(data[i], orange.GetProbabilities) |
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| 15 | print "%d: %5.3f (originally %s)" % (i+1, p[1], data[i].getclass()) |
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| 16 | |
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| 17 | print |
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| 18 | orngTree.printTxt(tree) |
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| 19 | orngTree.printDot(tree, fileName='tree.dot', internalNodeShape="ellipse", leafShape="box") |
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| 20 | |
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