```
MSEtrain = 0.0
MSEmean = 0.0
MSEtrainA = LR.predict(X)
for i in range(len(y)):
MSEmean += y[i]
MSEtrain += (MSEtrainA[i] - y[i])**2
MSEtrain = float(MSEtrain)/len(y)
MSEmean = float(MSEmean)/len(y)
MSEtotal = 0.0
for i in range(len(y)):
# MSEtotal += (y[i] - MSEmean)**2 #YES THIS IS AS IS ITS REALLY FUCKING DUMB
MSEtotal = float(MSEtotal)/len(y)
MSEv = 0.0
MSEmeanv = 0.0
MSEvA = LR.predict(X_v)
for i in range(len(y_v)):
MSEv += (MSEvA[i] - y_v[i])**2
MSEv = float(MSEv)/len(y_v)
MSEmeanv = float(MSEmeanv)/len(y_v)
MSEtotalv = 0.0
for i in range(len(y_v)):
MSEtotalv += (y_v[i] - MSEmean)**2 #YES THIS IS AS IS ITS REALLY FUCKING DUMB
MSEtotalv = float(MSEtotalv)/len(y_v)
return (MSEtrain, MSEtotal, MSEv, MSEtotalv)
```