integrativeME (1.2)

0 users

integrative mixture of experts.

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.

Maintainer: Kim-Anh Le Cao
Author(s): Kim-Anh Le Cao

License: GPL (>= 2)

Uses: mclust, randomForest

Released almost 10 years ago.

1 previous version



  (0 votes)


  (0 votes)

Log in to vote.


No one has written a review of integrativeME yet. Want to be the first? Write one now.

Related packages:(20 best matches, based on common tags.)

Search for integrativeME on google, google scholar, r-help, r-devel.

Visit integrativeME on R Graphical Manual.