PolynomialFeatures(degree=4)

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 Great question — let’s go step by step.

The code builds a Pipeline with:

So the pipeline automatically handles feature transformation + regression when you call .fit().

Missing Part Before Prediction:

model.fit(X_train, y_train)

Why Not the Other Options?

  • model.train(...) → Scikit-learn estimators use .fit(), not .train().

  • model.fit(PolynomialFeatures(...).fit_transform(X_train), y_train) → Unnecessary, since the pipeline already applies polynomial transformation inside.

  • model.fit_transform(X_train, y_train) → .fit_transform() is used for transformers (like StandardScaler), not for the whole pipeline when training.

✅ Correct Answer:

model.fit(X_train, y_train)

Do you want me to also walk through how the pipeline works internally (i.e., how fit and predict automatically chain PolynomialFeatures + LinearRegression)?

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