On Potts Model Clustering , Kernel K-means , and Density Estimation

@inproceedings{Murua2006OnPM,
  title={On Potts Model Clustering , Kernel K-means , and Density Estimation},
  author={Alejandro Murua and Larissa Stanberry and Werner Stuetzle},
  year={2006}
}
Many clustering methods, such as K -means, kernel K -means, and MNcut clustering, follow the same recipe: (i) choose a measure of similarity between observations; (ii) define a figure of merit assigning a large value to partitions of the data that put similar observations in the same cluster; and (iii) optimize this figure of merit over partitions. Potts model clustering represents an interesting variation on this recipe. Blatt, Wiseman, and Domany defined a new figure of merit for partitions… CONTINUE READING