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35 lines
1.3 KiB
Ruby
35 lines
1.3 KiB
Ruby
require 'rubygems'
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require 'decisiontree'
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# ---Discrete-----------------------------------------------------------------------------------------
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# Read in the training data
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training, attributes = [], nil
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File.open('data/discrete-training.txt','r').each_line { |line|
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data = line.strip.split(',')
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attributes ||= data
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training.push(data.collect {|v| (v == 'will buy') || (v == "won't buy") ? (v == 'will buy' ? 1 : 0) : v})
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}
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# Remove the attribute row from the training data
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training.shift
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# Instantiate the tree, and train it based on the data (set default to '1')
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dec_tree = DecisionTree::ID3Tree.new(attributes, training, 1, :discrete)
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dec_tree.train
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#---- Test the tree....
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# Read in the test cases
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# Note: omit the attribute line (first line), we know the labels from the training data
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test = []
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File.open('data/discrete-test.txt','r').each_line { |line| data = line.strip.split(',')
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test.push(data.collect {|v| (v == 'will buy') || (v == "won't buy") ? (v == 'will buy' ? 1 : 0) : v})
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}
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# Let the tree predict the output and compare it to the true specified value
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test.each { |t| predict = dec_tree.predict(t); puts "Predict: #{predict} ... True: #{t.last}"; }
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# Graph the tree, save to 'discrete.png'
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dec_tree.graph("discrete")
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