code: function getCurrentClass(currentCase, mean, classes) {
    var maxProbability = 0;
    var predictedClass = -1;
  
    // going through all precalculated values for the classes
    for (var i = 0; i < classes.length; ++i) {
      var currentProbability = classes[i][0]; // initialize with the prior probability
      for (var j = 1; j < classes[0][1].length + 1; ++j) {
        currentProbability += calculateLogProbability(
          currentCase[j - 1],
          mean[i][j - 1],
          classes[i][j][0],
          classes[i][j][1]
        );
      }
  
      currentProbability = Math.exp(currentProbability);
      if (currentProbability > maxProbability) {
        maxProbability = currentProbability;
        predictedClass = i;
      }
    }
  
    return predictedClass;
  }
docs: @private
  Function the retrieves a prediction with one case.
  
  @param {Array} currentCase
  @param {Array} mean - Precalculated means of each class trained
  @param {Array} classes - Precalculated value of each class (Prior probability and probability function of each feature)
  @return {number}