Markov Chains, Computer Science, Programming, Probability, Problem Solving.
sklearn.model_selection import train_test_split from sklearn.tree import DecisionTreeRegressor import pandas as pd class MarkovChainCreator: def __init__(self, states): self.states = states self.state_number = len(states) self.state_possibilities = {} x = random.randint(250, 300) self.scores =