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x = [x for x, y in training_process]
y = [y for x, y in training_process]
x = x[::10]
y = y[::10]
plt.figure(figsize=((16,4)))
plt.plot(x, np.sqrt(y)) ????
print("\nFinding Error on test set...\n")
msef=0.0
for i1 in range(len(i)):
for i2 in range(len(j)):
if R1.item(i[i1],j[i2])!=0:
msef = msef + (R1.item((i[i1],j[i2]))-(L).item((i[i1],j[i2])))2
msef = (msef/(len(j)*len(i))) ????
print("RMSE f=",msef0.5)
mse = self.mse()
......
def mse(self):
...................
return np.sqrt(error) ???
x = [x for x, y in training_process]
y = [y for x, y in training_process]
x = x[::10]
y = y[::10]
plt.figure(figsize=((16,4)))
plt.plot(x, np.sqrt(y)) ????
print("\nFinding Error on test set...\n")
msef=0.0
for i1 in range(len(i)):
for i2 in range(len(j)):
if R1.item(i[i1],j[i2])!=0:
msef = msef + (R1.item((i[i1],j[i2]))-(L).item((i[i1],j[i2])))2
msef = (msef/(len(j)*len(i))) ????
print("RMSE f=",msef0.5)