work process k-means algorithm is as follows: First, choose k objects from n data objects as the initial cluster centers while for the rest of the other objects, according to the similarity (distance) with those of their cluster centers, They were assigned to the most similar (represented by the cluster center) clustering then calculated for each cluster received new cluster center (the cluster mean all objects) repeats this process Until the beginning of a standard measure function convergence. MSE is generally used as the standard measure function k clustering has the following characteristics: each cluster itself as compact as possible, and to separate between the clusters as possible. Here is what I wrote the source code.

K_Means.java

• We are an exchange download platform that only provides communication channels. The downloaded content comes from the internet. Except for download issues, please Google on your own.
• The downloaded content is provided for members to upload. If it unintentionally infringes on your copyright, please contact us.
• Please use Winrar for decompression tools
• If download fail, Try it againg or Feedback to us.
• If downloaded content did not match the introduction, Feedback to us，Confirm and will be refund.
• Before downloading, you can inquire through the uploaded person information

Nothing．