Method: RCPNetwork::DanglingModifiers.predict_from_data

Defined in:
lib/RCP_Network.rb

.predict_from_data ⇒ Object

Main decision tree



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# File 'lib/RCP_Network.rb', line 60

def self.predict_from_data
  require "decisiontree"
  
  input = File.read("data/input/modifier_ratio.txt").to_f
  
  attributes = ["Modifier"]
  
  training = [
    [13.75,      'Very Low'], [20.625, 'Somewhat Low'], [27.5,     'Normal Low'],
    [37.3125,      'Medium'], [54.0,           'High'], [67.5,         'Urgent'],
    [81.0,         'Danger'], [94.5,       'Critical'], [108.0,     'Automatic'],
  ]
  
  dec_tree = DecisionTree::ID3Tree.new(attributes, training, 1, :continuous)
  dec_tree.train
  
  test = [input]
  
  decision = dec_tree.predict(test)
  
  if decision == "Automatic" or 108.8
    RCPNetwork::DanglingModifiers.make_choice
  else
    RCPNetwork::DanglingModifiers.random_modifier
  end
  
  new_input = input += 0.5
  
  open("data/input/modifier_ratio.txt", "w") { |f|
    f.puts new_input
  }
end