learningRateEnd=.0,
regulationRate=.02)
train5_Time = time.time() - start_time
start_time = time.time()
myNet20.Train(dataset,
target,
iterationCount=20,
learningRateStart=.6,
learningRateEnd=.0,
regulationRate=.02)
train20_Time = time.time() - start_time
# **************************************** Print Metrics *************************************************************
from sklearn.metrics import mean_squared_error
t5, o5 = ev.GetPredictions(myNet5, test_dataset, test_target)
t20, o20 = ev.GetPredictions(myNet20, test_dataset, test_target)
print(" ")
print(
"---------------------------------------------------------------------------------"
)
print(
"------------------------------ Bike Sharing Data Set ----------------------------"
)
print(">>>>>>>>>>>>> 5 hidden units")
print("mean_squared_error : {}".format(round(mean_squared_error(t5, o5), 6)))
print("Root_MSE : {}".format(
round(math.sqrt(mean_squared_error(t5, o5)), 6)))
print("Training Time : {} Seconds".format(round(train5_Time, 3)))
print(
