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While using K-means clustering, we scale the variables before we do clustering. This is done primarily to a. make the model less susceptible to outliers b. convert the data to same scale hence variables which are of different units are given equal importance c. avoid multicollinearity among the variables d. treat missing values to make the data more robust for analysis
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