Spam Classifier - Calculate the Precision and Recall for the model

Finally, we will calculate the precision and recall for the model that we created in the previous step.

INSTRUCTIONS

First, we will import precision_score and recall_score from Scikit-learn:

from sklearn.metrics import precision_score, << your code goes here >>

Put the test set through the pipeline we created:

X_test_transformed = << your code goes here >>.transform(X_test)

Fit our model on the test set:

log_clf = LogisticRegression(solver="lbfgs", random_state=42)
log_clf.fit(X_train_transformed, y_train)

Make our predictions using predict on the transformed test dataset:
```
y_pred = log_clf.<< your code goes here >>(X_test_transformed)
```

Finally, we will calculate and print the Precision and Recall scores of our model:

print("Precision: {:.2f}%".format(100 * precision_score(y_test, y_pred)))
print("Recall: {:.2f}%".format(100 * recall_score(y_test, y_pred)))

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