Data Preprocessing Quiz (Easy)

Which of the following is NOT a feature scaling technique?

In the context of missing data, what does ‘imputation’ mean?

What is the primary goal of data preprocessing?

What does feature scaling help with in machine learning models?

In the context of feature encoding, what does one-hot encoding achieve?

What is the effect of standardization (Z-score normalization) on a dataset?

Which of the following is a disadvantage of using Min-Max Scaling?

What is the purpose of discretization in data preprocessing?

Why is it important to avoid data leakage during the data preprocessing phase?

What is the main difference between normalization and standardization?

In machine learning, ‘noise’ in the dataset refers to:

Bootstrapping is used for: