Explore the significance of data normalization in machine learning model training. Learn how normalization ensures consistent feature scales for enhanced model accuracy and performance.
Question
You need to train and test your model. You prepare data for model training. Several of your numeric features have different scales: the first feature has a minimum value of 0.253 and a max of 0.987, the second one – from 12 to 124, and the last one – from 13545 to 56798. You need to bring them to a common scale.
You decide to normalize your data to address this problem.
Does this decision help you to achieve your goal?
A. Yes
B. No
Answer
A. Yes
Explanation
Yes, normalizing the data helps achieve the goal of bringing numeric features with varying scales onto a common scale. Normalization scales the features, ensuring that each falls within a consistent range, preventing certain features from dominating due to larger scales.
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