Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
The RKLT is a lossless approximation to the KLT, and has been recently employed for progressive lossy-to-lossless coding of hyperspectral images. Both yield very good coding perfo...
Story clustering is a critical step for news retrieval, topic mining, and summarization. Nonetheless, the task remains highly challenging owing to the fact that news topics exhibit...
In this paper, an HMM-embedded unsupervised learning approach is proposed to detect the music events by grouping the similar segments of the music signal. This approach can cluste...