What is the role of feature scaling in machine learning?
Practice Questions
Q1
What is the role of feature scaling in machine learning?
To increase the number of features
To ensure all features contribute equally to the model
To reduce the size of the dataset
To improve interpretability
Questions & Step-by-Step Solutions
What is the role of feature scaling in machine learning?
Step 1: Understand that features are the different inputs or variables used in a machine learning model.
Step 2: Realize that features can have different ranges of values (e.g., age from 0-100 and income from 0-100,000).
Step 3: Know that if features have different ranges, the model may give more importance to features with larger values.
Step 4: Learn about feature scaling, which adjusts the values of features to a similar range.
Step 5: Identify two common methods of feature scaling: standardization (making values have a mean of 0 and a standard deviation of 1) and normalization (scaling values to a range of 0 to 1).
Step 6: Understand that feature scaling helps the model learn better and faster by ensuring all features contribute equally.
