Background: The recent advancement of microarray technology with lower noise and better affordability makes it possible to determine expression of several thousand genes simultane...
Raja Loganantharaj, Satish Cheepala, John Clifford
In this paper, we undertake a performance study of some recent algorithms for geometric pattern matching. These algorithms cover two general paradigms for pattern matching; alignm...
Martin Gavrilov, Piotr Indyk, Rajeev Motwani, Sure...
Clustering is ill-defined. Unlike supervised learning where labels lead to crisp performance criteria such as accuracy and squared error, clustering quality depends on how the cl...
Rich Caruana, Mohamed Farid Elhawary, Nam Nguyen, ...
We have developed a biologically-motivated, unsupervised way of grouping together images whose salient regions of interest (ROIs) are perceptually similar regardless of the visual...
Gustavo B. Borba, Humberto R. Gamba, Oge Marques, ...
In this article, a novel concept is introduced by using both unsupervised and supervised learning. For unsupervised learning, the problem of fuzzy clustering in microarray data as ...