A hybrid unsupervised and supervised clustering applied to microarray data

Raul Malutan, Pedro Gomez Vilda, Monica Borda
2013 International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems  
Clustering methods have been often applied to large data with the main purpose of reducing the dimension, time computation and identifying clusters with similar behavior. This work presents a state-of-the-art in unsupervised clustering and cluster validation. It proposes a method for hybrid bi-clustering of microarray data combined with a supervised validation for determining the optimal amount of clusters of genes.
doi:10.11601/ijates.v2i3.21 fatcat:uvuizkmb4nfm7k62v3cmaif34m