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Fix infinite recursion.
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@@ -69,9 +69,14 @@ module DecisionTree
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# return classification if all examples have the same classification
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return data.first.last if data.classification.uniq.size == 1
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# Choose best attribute (1. enumerate all attributes / 2. Pick best attribute)
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# Choose best attribute:
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# 1. enumerate all attributes
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# 2. Pick best attribute
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# 3. If attributes all score the same, then pick a random one to avoid infinite recursion.
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performance = attributes.collect { |attribute| fitness_for(attribute).call(data, attributes, attribute) }
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max = performance.max { |a,b| a[0] <=> b[0] }
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min = performance.min { |a,b| a[0] <=> b[0] }
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max = performance.shuffle.first if max == min
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best = Node.new(attributes[performance.index(max)], max[1], max[0])
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best.threshold = nil if @type == :discrete
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@used.has_key?(best.attribute) ? @used[best.attribute] += [best.threshold] : @used[best.attribute] = [best.threshold]
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@@ -74,4 +74,19 @@ describe describe DecisionTree::ID3Tree do
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Then { tree.predict([2, "blue"]).should == "not angry" }
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end
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describe "infinite recursion case" do
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Given(:labels) { [:a, :b, :c] }
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Given(:data) do
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[
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["a1", "b0", "c0", "RED"],
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["a1", "b1", "c1", "RED"],
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["a1", "b1", "c0", "BLUE"],
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["a1", "b0", "c1", "BLUE"]
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]
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end
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Given(:tree) { DecisionTree::ID3Tree.new(labels, data, "RED", :discrete) }
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When { tree.train }
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Then { tree.predict(["a1","b0","c0"]).should == "RED" }
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end
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end
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