Answer
Normalization scales values to 0–1.
Standardization gives mean 0 and std 1.
Ensures equal feature contribution.
Standardization gives mean 0 and std 1.
Ensures equal feature contribution.
Quick Answer
Normalization scales to [0,1]: (x - min)/(max - min) with MinMaxScaler. Standardization scales to mean=0, std=1: (x - mean)/std with StandardScaler. Use standardization for algorithms that assume normal distribution (linear regression, SVM, neural nets). Normalization for bounded ranges. Always fit scaler on training data only, then transform test data to prevent data leakage.
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SugharaIQ Editorial Team
Verified Answer
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Source: SugharaIQ