In feature engineering, what does normalization refer to?
Practice Questions
Q1
In feature engineering, what does normalization refer to?
Scaling features to a common range
Removing outliers from the dataset
Encoding categorical variables
Selecting important features
Questions & Step-by-Step Solutions
In feature engineering, what does normalization refer to?
Step 1: Understand that features are the individual measurable properties or characteristics of the data.
Step 2: Realize that different features can have different ranges of values (e.g., one feature might range from 1 to 100, while another ranges from 0 to 1).
Step 3: Know that normalization is a technique used to adjust these features so they can be compared more easily.
Step 4: Learn that normalization typically scales the values of features to a specific range, commonly between 0 and 1.
Step 5: Understand that this helps improve the performance of machine learning algorithms by ensuring that no single feature dominates others due to its scale.
