Class: DGaffML::Model

Inherits:
Object
  • Object
show all
Defined in:
lib/dgaff_ml/model.rb

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(client, model_response) ⇒ Model

Returns a new instance of Model.



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# File 'lib/dgaff_ml/model.rb', line 4

def initialize(client, model_response)
  @client = client
  @model = model_response
  @dataset_id = @model["id"]
  @user_id = @model["user_id"]
end

Instance Attribute Details

#model ⇒ Object

Returns the value of attribute model.



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# File 'lib/dgaff_ml/model.rb', line 3

def model
  @model
end

Instance Method Details

#cast_val(value, directive) ⇒ Object 



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# File 'lib/dgaff_ml/model.rb', line 94

def cast_val(value, directive)
  if directive == "Integer"
    return value.to_i
  elsif directive == "Float"
    return value.to_f
  elsif directive == "Time"
    if value.length == 10 and value.scan(/\d/).count == 10
      return Time.at(value).to_i
    elsif value.length == 13 and value.scan(/\d/).count == 13
      return Time.at(value).to_i
    else
      return Chronic.parse(value).to_i
    end
  elsif directive == "Text" or directive == "Phrase"
    return clean_str(value).split(" ").collect{|word| Stemmer::stem_word(word)}
  elsif directive == "Categorical"
    return value
  end
end

#clean_str(string) ⇒ Object 



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# File 'lib/dgaff_ml/model.rb', line 67

def clean_str(string)
  string.
  gsub(/[^A-Za-z0-9(),!?\'\`]/, " ").
  gsub("  ", " ").
  gsub("\'s", " \'s").
  gsub("", "").
  gsub("\'ve", " \'ve").
  gsub("n\'t", " n\'t").
  gsub("\'re", " \'re").
  gsub("\'d", " \'d").
  gsub("\'ll", " \'ll").
  gsub(",", " , ").
  gsub("!", " ! ").
  gsub("\(", " \\( ").
  gsub("\)", " \\) ").
  gsub(" \\\(  \\\(  \\\( ", " \(\(\( ").
  gsub(" \\\)  \\\)  \\\) ", " \)\)\) ").
  gsub("\?", " \? ").
  gsub(/\s{2,}/, " ").
  gsub(Regexp.new("http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\(\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+"), "<URL/>").
  gsub("www", " ").
  gsub("com", " ").
  gsub("org", " ").
  strip.
  downcase
end

#convert(rows, model_keys, model_classes) ⇒ Object 



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# File 'lib/dgaff_ml/model.rb', line 34

def convert(rows, model_keys, model_classes)
  transposed = rows.transpose
  detexted = []
  labels = []
  transposed.each_with_index do |col, i|
    if model_classes[i] == "Phrase" || model_classes[i] == "Text"
      self.model["conversion_pipeline"][model_keys[i]]["unique_terms"].each do |term|
        counted = []
        col.each do |row|
          row = [row.to_s] if row.nil?
          counted << row.count(term)
        end
        detexted << counted
      end
    elsif model_classes[i] == "Categorical"
      counted = []
      col.each do |val|
        counted << self.model["conversion_pipeline"][model_keys[i]]["unique_terms"].index(val.to_s)
      end
      detexted << counted
    else
      conversion_pipeline = self.model["conversion_pipeline"][model_keys[i]]
      replaced = col.collect{|r| r||conversion_pipeline["average"]}
      dist = conversion_pipeline["max"]-conversion_pipeline["min"]
      detexted << replaced
      detexted << replaced.collect{|r| (r-conversion_pipeline["min"]).to_f/dist} if dist > 0
      detexted << replaced.collect{|r| (r-conversion_pipeline["average"]).to_f/conversion_pipeline["stdev"]} if conversion_pipeline["stdev"] > 0
      detexted << replaced.collect{|r| r.abs}
    end
  end
  return detexted.transpose
end

#predict(obs) ⇒ Object 



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# File 'lib/dgaff_ml/model.rb', line 11

def predict(obs)
  predictions = @client.predict(@dataset_id, translate_obs(obs))
  if self.model["conversion_pipeline"].keys.include?("label")
    return predictions.collect{|x| self.model["conversion_pipeline"]["label"][x]}
  else
    return predictions
  end
end

#translate_obs(obs) ⇒ Object 



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# File 'lib/dgaff_ml/model.rb', line 20

def translate_obs(obs)
  model_keys = (self.model["conversion_pipeline"].keys-["label"]).sort_by(&:to_i)
  model_classes = model_keys.collect{|k| self.model["col_classes"][k.to_i]}
  translated_rows = []
  obs.each do |row|
    translated_row = []
    row.each_with_index do |el, i|
      translated_row << cast_val(el, model_classes[i])
    end
    translated_rows << translated_row
  end
  self.convert(translated_rows, model_keys, model_classes)
end