What does y_test[0] means exactly?

Asked Dec 05 '22 at 18:30

Active Dec 05 '22 at 18:30

Viewed 10 times

why y_test[0] works fine here

from sklearn.linear_model import LinearRegression

lr = LinearRegression()
lr.fit(X_train, y_train)
predictions = lr.predict(X_test)

print("Actual value of the house:- ", y_test[0]) 
print("Model Predicted Value:- ", predictions[0])

but y_test[1] can't.

here shape of y_test shape is (102,)

so by the array logic it should give me value upto 102.

y_test[0] y_test[1] . . . . . y_test[102]

but only y_test[0] works.

I thought y_test[1] should work the same as y_test[0] but something is wrong with that idk what. what does y_test[0] means exactly?

asked Dec 05 '22 at 18:30

Victor Ran

What does it happens when you enter `y_test[1]`? If there's an error, what's the error message? Maybe `KeyError: 1`? – Ignatius Reilly Dec 05 '22 at 18:35
BTW, if y_test has 102 elements, it should index up to `y_test[101]`. – Ignatius Reilly Dec 05 '22 at 18:37
It's a key error – Victor Ran Dec 05 '22 at 18:38
KeyError Traceback (most recent call last) /usr/local/lib/python3.8/dist-packages/pandas/core/indexes/base.py in get_loc(self, key, method, tolerance) 3360 try: -> 3361 return self._engine.get_loc(casted_key) 3362 except KeyError as err: – Victor Ran Dec 05 '22 at 18:38
@IgnatiusReilly yes – Victor Ran Dec 05 '22 at 18:41
Probably there's no y_test with index 1, maybe that index number went to the training split? – Ignatius Reilly Dec 05 '22 at 18:42

What does y_test[0] means exactly?

0 Answers0