scripts/builtin/getAccuracy.dml

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# compute the weighted and simple accuracy for given predictions

# Built-in function Implements Multiple Imputation using Chained Equations (MICE) 
#
# INPUT PARAMETERS:
# ---------------------------------------------------------------------------------------------
# NAME            TYPE    DEFAULT     MEANING
# ---------------------------------------------------------------------------------------------
# y               Double    ---        Ground truth (Actual Labels)
# yhat            Double    ---        predictions (Predicted labels)
# isWeighted      Boolean   FALSE      flag for weighted or non-weighted accuracy calculation 
# ---------------------------------------------------------------------------------------------
 

#Output(s)
# ---------------------------------------------------------------------------------------------
# NAME                  TYPE    DEFAULT     MEANING
# ---------------------------------------------------------------------------------------------
# accuracy               Double   ---       accuracy of the predicted labels


m_getAccuracy = function(Matrix[Double] y, Matrix[Double] yhat, Boolean isWeighted = FALSE)
return (Double accuracy)
{
  if(isWeighted)
  {
    sum = sum(y == yhat)
    accuracy = (sum/nrow(y)) * 100
  }
  else 
  {
    n = nrow(y)
    classes = table(y, 1)
    class_weight = n/(nrow(classes) * classes)
    resp = matrix(0, nrow(y), nrow(classes))
    resp = resp + t(seq(1, nrow(classes)))

    respY = resp == y
    respYhat = resp == yhat
    
    pred = respY * respYhat
    classes = replace(target = classes, pattern = 0, replacement = 1)
    accuracy = mean(colSums(pred)/t(classes)) * 100
  }

}