updated rotation forest models

topepo · Oct 25, 2016 · afcaa29 · afcaa29
1 parent d6cb9ea
commit afcaa29
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Showing 3 changed files with 9 additions and 4 deletions.
diff --git a/models/files/rotationForest.R b/models/files/rotationForest.R
@@ -5,10 +5,12 @@ modelInfo <- list(label = "Rotation Forest",
                                           class = rep("numeric", 2),
                                           label = c("#Variable Subsets", "Ensemble Size")),
                   grid = function(x, y, len = NULL, search = "grid") {
+                    feas_k <- 1:15
+                    feas_k <- feas_k[ncol(x)%%feas_k == 0]
                     if(search == "grid") {
-                      out <- expand.grid(K = 1:min(len, ncol(x)-1), L = (1:len)*3) 
+                      out <- expand.grid(K = feas_k[1:min(len, length(feas_k))], L = (1:len)*3) 
                     } else {
-                      out <- data.frame(K = sample(1:min(len, ncol(x)-1), size = len, replace = TRUE), 
+                      out <- data.frame(K = sample(feas_k, size = len, replace = TRUE), 
                                         L = sample(1:100, size = len, replace = TRUE))
                     }
                     out

diff --git a/models/files/rotationForestCp.R b/models/files/rotationForestCp.R
@@ -5,12 +5,14 @@ modelInfo <- list(label = "Rotation Forest",
                                           class = rep("numeric", 3),
                                           label = c("#Variable Subsets", "Ensemble Size", "Complexity Parameter")),
                   grid = function(x, y, len = NULL, search = "grid") {
+                    feas_k <- 1:15
+                    feas_k <- feas_k[ncol(x)%%feas_k == 0]
                     if(search == "grid") {
-                      out <- expand.grid(K = 1:min(len, ncol(x)-1), 
+                      out <- expand.grid(K = feas_k[1:min(len, length(feas_k))], 
                                          L = (1:len)*3,
                                          cp = unique(seq(0, .1, length = len)))
                     } else {
-                      out <- data.frame(K = sample(1:min(len, ncol(x)-1), size = len, replace = TRUE), 
+                      out <- data.frame(K = sample(feas_k, size = len, replace = TRUE), 
                                         L = sample(10:100, size = len, replace = TRUE),
                                         cp = runif(len, 0, .1))
                     }

diff --git a/pkg/caret/inst/NEWS.Rd b/pkg/caret/inst/NEWS.Rd
@@ -16,6 +16,7 @@
 		\item A variable importance method was added for boosted generalized linear models \issue{493}
 		\item \code{preProcess} now has an option to filter out highly correlated predictors. 
 		\item \code{trainControl} now has additional options to modify the parameters of near-zero variance and correlation filters. See the \code{preProcOptions} argument. 
+		\item The \code{rotationForest} and \code{rotationForestCp} methods were revised to evaluate only \emph{feasible} values of the parameter \code{K} (the number of variable subsets). The underlying \code{rotationForest} function reduces this parameter until values of \code{K} divides evenly into the number of parameters.   
 	}
 }