from env import Env from myDQN import DeepQNetwork from sklearn.model_selection import KFold import numpy as np import tensorflow as tf import time start_time = time.time() # 1.47 current_Env = Env() current_Env.readData() current_Env.processing() current_Env.appendSeq() cross_validation = 4 percisionListPart = [] percisionListAll = [] kf = KFold(n_splits=cross_validation) cvIndex = 1 for trainUserIdRange, testUserIdRange in kf.split(np.array(range(current_Env.numUser))): #current_Env.numUser # trainUserIdRange/testUserIdRange both are lists of UserId # initial network for each cv RL = DeepQNetwork( current_Env.n_actions, 164, learning_rate=0.01, reward_decay=0.9, e_greedy=0.9, replace_target_iter=200, memory_size=5000, batch_size=320,