Chapter 6, exercise 8

Hi,
I am wondering in exercise 8 ln 24, should the tree classifier predict for `X_mini_test` which has 7900 elements instead of `X_test` as below?

```python
for tree, (X_mini_train, y_mini_train) in zip(forest, mini_sets):
tree.fit(X_mini_train,y_mini_train)
y_pred = tree.predict(X_mini_test)
accuracy_scores.append(accuracy_score(y_mini_test, y_pred))
```

If yes, then `mini_sets` for test elements should be also added in the for loop in ln 23 like

```python
for mini_train_index,mini_test_index in rs.split(X_train):
X_mini_train=X_train[mini_train_index]
y_mini_train=y_train[mini_train_index]
X_mini_test=X_train[mini_test_index]
y_mini_test=y_train[mini_test_index]
mini_sets.append((X_mini_train,y_mini_train))
mini_sets_test.append((X_mini_test,y_mini_test))
```

Otherwise, predicting X_test in ln 25 is redundant since y_pred was calculated before in ln 24.

Thanks,