Package: integrativeME
Type: Package
Title: integrative mixture of experts
Version: 1.2
Date: 2009-09-29
Depends: R (>= 2.10), mclust, mixOmics, randomForest
Author: Kim-Anh Le Cao
Maintainer: Kim-Anh Le Cao <k.lecao@uq.edu.au>
Description: Mixture of experts models (Jacobs et al., 1991) were
        introduced to account for nonlinearities and other complexities
        in the data. It is based on a divide-and-conquer strategy.
        Mixture of experts are of interest due to their wide
        applicability and the advantages of fast learning via the
        expectation-maximization (EM) algorithm. We have extended and
        implemented mixture of experts to combine categorical clinical
        factors and continuous microarray data in a binary
        classification framework to analyze cancer studies. To provide
        a hybrid signature of clinical factors and gene markers, we
        propose to apply different gene selection procedures as a first
        step.
License: GPL (>= 2)
Packaged: 2012-07-23 10:09:21 UTC; ripley
Repository: CRAN
Date/Publication: 2012-07-23 10:35:32
