What is the purpose of feature scaling in machine learning?
Correct Answer: Feature scaling helps in improving model performance.
- Step 1: Understand that in machine learning, we use data with different features (like height, weight, age).
- Step 2: Realize that these features can have different ranges (for example, height in cm and weight in kg).
- Step 3: Know that when we calculate distances (like in clustering or nearest neighbors), features with larger ranges can dominate the calculations.
- Step 4: Learn that feature scaling adjusts the features to a similar range, so they contribute equally.
- Step 5: Recognize that this helps the model learn better and perform more accurately.
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