We investigate the performance of different classification models and their ability to recognize prostate cancer in an early state. We build ensembles of classification models in ...
The use of bagging is explored to create an ensemble of fuzzy classifiers. The learning algorithm used was ANFIS (Adaptive Neuro-Fuzzy Inference Systems). We compare results from b...
Juana Canul-Reich, Larry Shoemaker, Lawrence O. Ha...
— Cluster Ensembles is a framework for combining multiple partitionings obtained from separate clustering runs into a final consensus clustering. This framework has attracted mu...
We consider the issue of how to read out the information from nonstationary spike train ensembles. Based on the theory of censored data in statistics, we propose a ‘censored’ m...
Background: Ensemble attribute profile clustering is a novel, text-based strategy for analyzing a userdefined list of genes and/or proteins. The strategy exploits annotation data ...
J. R. Semeiks, A. Rizki, Mina J. Bissell, I. Saira...