Feature Engineering in Scikit-Learn

Test your ability to preprocess,scale,and select relevant features for ML models.

1. Which Scikit-Learn transformer is used for one-hot encoding categorical features?
2. Which of the following are valid imputation transformers in Scikit-Learn?
3. StandardScaler is appropriate for features with outliers, as it is robust to extreme values.
4. Name the Scikit-Learn class that chains multiple transformers into a single object (full name)
5. What does the MinMaxScaler transformer do?
6. Select all Scikit-Learn classes that can be used for scaling numerical features.
7. The fit() method of a transformer learns parameters from the training data, while transform() applies those parameters to new data.
8. What is the abbreviation for the technique that replaces missing values with the most frequent value in a column? (abbrev.)
9. Which class in Scikit-Learn allows applying different transformers to different columns of a DataFrame?
10. Name the Scikit-Learn transformer that scales features using median and IQR to be robust against outliers (full name)
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