Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-...
Christopher Leckie, James C. Bezdek, Kotagiri Rama...
- The activities and function of proteins can potentially be determined by protein sequence motifs. Therefore, obtaining the universally conserved and crossed protein family bounda...
We present a method for initialising the K-means clustering algorithm. Our method hinges on the use of a kd-tree to perform a density estimation of the data at various locations. ...
Abstract. Clustering is a problem of great practical importance in numerous applications. The problem of clustering becomes more challenging when the data is categorical, that is, ...
The ability to predict the quality of a software object can be viewed as a classification problem, where software metrics are the features and expert quality rankings the class lab...