from neural_net import NeuralNet
import random
badCompany = (688657, 3232342, 12, 18)
goodCompany = (150000, 25, 600000, 2)
bluetooth_implant = (1000000, 15, 6666667, 1
) # should be consistently lower than output model
ava_the_elephant = (50000, 15, 333333, 3) # somewhat successful product
scrub_daddy = (100000, 10, 1000000, 9) # most successful product
net = NeuralNet()
net.init_model()
print(net.checkPerformance())
def evaluate(company):
offer = net.predictOffer(company)
net.init_model()
return offer
def average(ls):
return sum(ls) / len(ls)
blue = [evaluate(bluetooth_implant) for i in range(2)]
#ava = [evaluate(ava_the_elephant) for j in range(50)]
#scrub = [evaluate(scrub_daddy) for k in range(50)]
print(blue)
#print(ava)
