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How to optimize the result of K means

Discussion in 'Education' started by 梁楷葳, Oct 8, 2018.

  1. 梁楷葳

    梁楷葳 Guest

    I am analyzing the data of abalone. My goal is to classify the data into three categories(premium, medium premium, and classic). Since it's an unlabeled dataset, so I utilized K means clustering to do it. My problem is, is there any way the optimize the result? I feel like the only analysis that I can do in the k means algorithm in R is km = kmeans(data,centers=3,nstart=25). Is there any parameter that I can tune in this algorithm. Please give me some suggestion?

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