Markov Chains, Computer Science, Programming, Probability, Problem Solving.
[x-50*_ for _ in range(len(states))] def assign_train(self): self.train_size = int(len(self.numericData) * 0.8) self.train, self.test = self.numericData[:self.train_size], self.numericData[self.train_size:] def assign_possibilities(self): probabilities = {} min_probability = 1 / len(self.states) #