Adding accuracy function

Author: miladsade96

machine_learning/linear discriminant analysis.py

@@ -162,3 +162,23 @@ def predict(x_items: list, means: list, variance: float, probabilities: list) ->
         # discriminant value is taken as the prediction, than we try to get index of that.
         predicted_index.append(l.index(max(l)))
     return predicted_index
+
+
+# Calculating Accuracy
+def accuracy(actual_y: list, predicted_y: list) -> float:
+    """ This function calculates the value of accuracy based-on predictions
+    :param actual_y:a list containing initial Y values generated by 'Y_gen' function
+    :param predicted_y: a list containing predicted Y values generated by 'predict' function
+    :return: percentage of accuracy
+    """
+    correct = 0     # initial value for number of correct predictions
+    # for loop iterates over one element of each list at a time (zip mode)
+    for i, j in zip(actual_y, predicted_y):
+        # if actual Y value equals to predicted Y value
+        if i == j:
+            # prediction is correct
+            correct += 1
+    # percentage of accuracy equals to number of correct predictions divided by number of
+    # all data and multiplied by 100
+    percentage = (correct / len(actual_y)) * 100
+    return percentage