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

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

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Question: While using K-means clustering, we scale the variables before we do clustering. This is done O treat missing values to make the data more robust

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