In active learning, one attempts to maximize classifier performance for a given number of labeled training points by allowing the active learning algorithm to choose which points...
Clustering has been one of the most widely studied topics in data mining and k-means clustering has been one of the popular clustering algorithms. K-means requires several passes ...
Abstract. Brain imaging provides a wealth of information that computers can explore at a massive scale. Categorizing the patterns of the human cortex has been a challenging issue f...
Zhong Yi Sun, Matthieu Perrot, Alan Tucholka, Deni...
Most commonly used inductive rule learning algorithms employ a hill-climbing search, whereas local pattern discovery algorithms employ exhaustive search. In this paper, we evaluat...
This paper proposes a novel clustering analysis algorithm based on principal component analysis (PCA) and self-organizing maps (SOMs) for clustering the gene expression patterns. T...