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,
