Title: Build, Deploy and Evaluate Hybrid Ensembles
Imports: randomForest, kernelFactory, ada, rpart, ROCR, nnet, e1071,
NMOF, GenSA, Rmalschains, pso, AUC, soma, genalg, reportr,
nnls, quadprog, tabuSearch, rotationForest, FNN, glmnet
Description: Functions to build and deploy a hybrid ensemble consisting of eight different sub-ensembles: bagged logistic regressions, random forest, stochastic boosting, kernel factory, bagged neural networks, bagged support vector machines, rotation forest, and bagged k-nearest neighbors. Functions to cross-validate the hybrid ensemble and plot and summarize the results are also provided. There is also a function to assess the importance of the predictors.
Packaged: 2015-05-28 15:33:55 UTC; michelballings

nnls, quadprog, tabuSearch, rotationForest, FNN, glmnet,
Author: Michel Ballings, Dauwe Vercamer, Matthias Bogaert, and Dirk Van den Poel
Description: Functions to build and deploy a hybrid ensemble consisting of different sub-ensembles such as bagged logistic regressions, random forest, stochastic boosting, kernel factory, bagged neural networks, bagged support vector machines, rotation forest, bagged k-nearest neighbors, and bagged naive Bayes. Functions to cross-validate the hybrid ensemble and plot and summarize the results are also provided. There is also a function to assess the importance of the predictors.

Author: Hugh Chipman, Rob Tibshirani, with tsvq code originally from Trevor Hastie
Description: hybrid hierarchical clustering via mutual clusters
Packaged: Tue Mar 21 09:33:27 2006; hchipman

Packaged: Thu Jul  6 09:33:04 2006; hchipman

Packaged: Sun Oct 21 00:23:08 2007; hornik

Packaged: Tue Apr  8 06:23:16 2008; hchipman

Author: Hugh Chipman, Rob Tibshirani, with tsvq code originally from

Description: Hybrid hierarchical clustering via mutual clusters.  A mutual cluster is a set of points closer to each other than to all other points.  Mutual clusters are used to enrich top-down hierarchical clustering.

Title: Stochastic Hybrid Models in Dynamic Networks
Imports: doParallel, foreach, ggplot2, GillespieSSA, parallel,
Description: Simulates stochastic hybrid models for transmission of infectious
diseases in dynamic networks. It is a metapopulation model in which each
node in the network is a sub-population and disease spreads within nodes
and among them, combining two approaches: stochastic simulation algorithm
or its approximations (Gillespie DT (2007)
approach, respectively. Movement among nodes are data based and can be
irregular. Equations that models spread within nodes are customizable and
there are two link types among nodes: migration and influence (commuting).
Authors@R: c(person(given = "Fernando", family = "S. Marques",
email = "fernandosix@gmail.com", role = c("aut", "cre")),
person(given = "Jose", family="H. H. Grisi-Filho",
email = "zegrisi@gmail.com", role = "aut"),
person(given = "Marcos", family = "Amaku",
email = "marcos.amaku@gmail.com", role = "aut"))
Maintainer: Fernando S. Marques <fernandosix@gmail.com>