Class: Dwarf::Classifier

Inherits:
Object
  • Object
show all
Defined in:
lib/dwarf/classifier.rb

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize ⇒ Classifier

Returns a new instance of Classifier.



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# File 'lib/dwarf/classifier.rb', line 7

def initialize()
  @examples, @example_attributes = {}, []
  @decision_tree = TreeNode.new("ROOT")
end

Instance Attribute Details

#classifier_logic ⇒ Object

Returns the value of attribute classifier_logic.



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# File 'lib/dwarf/classifier.rb', line 5

def classifier_logic
  @classifier_logic
end

#example_attributes ⇒ Object

Returns the value of attribute example_attributes.



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# File 'lib/dwarf/classifier.rb', line 4

def example_attributes
  @example_attributes
end

#examples ⇒ Object

Returns the value of attribute examples.



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# File 'lib/dwarf/classifier.rb', line 3

def examples
  @examples
end

Instance Method Details

#add_example(example_record, classification) ⇒ Object 



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# File 'lib/dwarf/classifier.rb', line 18

def add_example(example_record, classification)
  @examples[example_record]=classification
  @example_attributes |= example_record.attributes
end

#add_examples(example_hash) ⇒ Object 



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# File 'lib/dwarf/classifier.rb', line 12

def add_examples(example_hash)
  example_hash.each do |example, classification|
    add_example(example, classification)
  end
end

#classify(example) ⇒ Object 



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# File 'lib/dwarf/classifier.rb', line 23

def classify(example)
  return nil
end

#learn! ⇒ Object 



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# File 'lib/dwarf/classifier.rb', line 27

def learn!
  @decision_tree.examples = @examples.keys
  pending = []
  pending.push @decision_tree
  used_attributes = []
  until pending.empty?
    node = pending.pop
    if classification = homogenous_examples(node)
      node.classification = classification
    elsif no_valuable_attributes?(node) && node.parent
      node.parent.classification= expected_value(node.examples)
    elsif no_valuable_attributes?(node)
      classifier_logic = expected_value(node.examples)
    elsif false #stub branch
      #C4.5 would also allow for previously unseen classifications
      #dwarf's API dictates all classifications are known before learning
      #starts
    else
      infogains = {}
      (@example_attributes-used_attributes).each do |example_attribute|
        infogains[information_gain(node.examples,example_attribute)] = example_attribute
      end
      best_gain = infogains.keys.sort[0]
      best_attribute = infogains[best_gain]
      split(node,best_attribute).each {|child_node| pending.push(child_node)}
      used_attributes << best_attribute
    end
  end
  self.classifier_logic = codify_tree(@decision_tree)
  implement_classify
end