Method: Callidus::ExponentialRegression#train

Defined in:
lib/src/ExponentialRegression.rb

#trainObject



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# File 'lib/src/ExponentialRegression.rb', line 34

def train
    mean_x = @input.mean
    mean_lny = @output.inject(0.0) { |s, n|  s + Math.log(n) } / @output.size

    sum_xx = 0.0
    sum_xy = 0.0
    sum_yy = 0.0

    @input.each_index do |i|
        sum_xx += @input[i] * @input[i]
        sum_xy += @input[i] * Math.log(@output[i])
        sum_yy += Math.log(@output[i]) * Math.log(@output[i])
    end

    sum_xx = (sum_xx / @input.size) - (mean_x * mean_x)
    sum_xy = (sum_xy / @input.size) - (mean_x * mean_lny)
    sum_yy = (sum_yy / @output.size) - (mean_lny * mean_lny)

    @b = sum_xy / sum_xx
    @a = 2.7182818284590452353602 ** (mean_lny - b * mean_x)

    @predicted_output = @input.map { |x| (@a * (2.7182818284590452353602 ** (@b * x))).round(3) }

    @correlation = (sum_xy / (Math.sqrt(sum_xx) * Math.sqrt(sum_yy))).round(3)

    @trained = true

    @a = @a.round(3)
    @b = @b.round(3)

    self.find_standard_error
end