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# The naiveBaysePredict-function predicts the scoring with a naive Bayes model.
#
# INPUT:
# ---------------------------------------------------------------------------------------
# X     Matrix of test data with N rows.
# P     Class priors, One dimensional column matrix with N rows.
# C     Class conditional probabilities, matrix with N rows
# ---------------------------------------------------------------------------------------
#
# OUTPUT:
# ---------------------------------------------------------------------------------------
# Y     A matrix containing the top-K item-ids with highest predicted ratings.
# YRaw  A matrix containing predicted ratings.
# ---------------------------------------------------------------------------------------

m_naiveBayesPredict = function(Matrix[Double] X, Matrix[Double] P, Matrix[Double] C)
 return (Matrix[Double] YRaw, Matrix[Double] Y)
{
  numRows = nrow(X)
  model = cbind(C, P)

  ones = matrix(1, rows=numRows, cols=1);
  X_w_ones = cbind(X, ones);
  YRaw = X_w_ones %*% t(log(model));
  Y = rowIndexMax(YRaw);
}