Markov Chains, Computer Science, Programming, Probability, Problem Solving.
numericData.append(score) self.numericData = numericData self.assign_train() def transform_predictions(self): predData = [] for i in range(len(self.predictions)): score = 0 for j in range(1, i + 1): score += self.scores[self.states.index(self.predictions[i])] predData.append(score)