Use the model created in the previous step to make predictions on the test set:
Use the model to predict the test data. First you need to pass the test data through the pipeline and store it in X_test, then predict it and store it in y_pred:
X_test = preprocess_pipeline.transform(<< your code goes here >>)
y_pred = svm_clf.predict(<< your code goes here >>)
Note - Having trouble with the assessment engine? Follow the steps listed here
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