Merge pull request #20 from andrie/ridge-regression

Added ridge regression

R/rxRidgeReg.R

@@ -0,0 +1,58 @@
+#' Fits ridge regression model.
+#' 
+#' Fits ridge regression model using the correlation matrix.  Supports estimation of multiple values of the regularisation coefficient (lambda).
+#' 
+#' @param formula Model formula
+#' @param data Data frame or XDF
+#' @param lambda Regularisation coefficient.  Can be a single value or a vector.
+#' @param ... Passed to \code{\link[RevoScaleR]{rxCovCor}}
+#' @references http://blog.revolutionanalytics.com/2014/03/extending-revoscaler-ridge-regression.html
+#' @author Derek McRae Norton
+#' @export
+#' 
+rxRidgeReg <- function(formula, data, lambda, ...) {
+  myTerms <- all.vars(formula)
+  newForm <- as.formula(paste("~", paste(myTerms, collapse = "+")))
+  myCor <- rxCovCor(newForm, data = data, type = "Cor", ...)
+  n <- myCor$valid.obs
+  k <- nrow(myCor$CovCor) - 1
+  bridgeprime <- do.call(rbind, lapply(lambda, 
+                                       function(l) qr.solve(myCor$CovCor[-1,-1] + l*diag(k), 
+                                                            myCor$CovCor[-1,1])))
+  bridge <-  myCor$StdDevs[1] * sweep(bridgeprime, 2, 
+                                      myCor$StdDevs[-1], "/")
+  bridge <- cbind(t(myCor$Means[1] - 
+                      tcrossprod(myCor$Means[-1], bridge)), bridge)
+  rownames(bridge) <- format(lambda)
+  obj <- bridge
+  class(obj) <- c("rxRidgeReg", "matrix")
+  obj
+}
+
+
+plot.rxRidgeReg <- function(dat, scale=FALSE){
+  if(colnames(dat)[1] == "") colnames(dat)[1] <- "Intercept"
+  if(scale) {
+    scaleValue <- apply(dat, 2, function(x){
+      max(max(x), abs(min(x)))
+    })
+    dat <- scale(dat, center=FALSE, scale=scaleValue)
+    ylab <- "Scaled coefficient"
+  } else {
+    ylab <- "Coefficient"
+  }
+
+  matplot(x=as.numeric(rownames(dat)), y=dat, type="l", bty="n",
+          ylab=ylab, xlab="lambda")
+
+}
+
+#' @examples
+#' data(swiss)
+#' frm <- formulaExpand(Fertility ~ ., data=swiss)
+#' rxRidgeReg(frm, swiss, lambda=0)
+#' model <- rxRidgeReg(frm, swiss, lambda=c(seq(from=0, to=1, by=0.05)))
+#' plot(model)
+#' plot(model, scale=TRUE)
+
+

man/rxRidgeReg.Rd

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+\name{rxRidgeReg}
+\alias{rxRidgeReg}
+\title{Fits ridge regression model.}
+\usage{
+rxRidgeReg(formula, data, lambda, ...)
+}
+\arguments{
+  \item{formula}{Model formula}
+
+  \item{data}{Data frame or XDF}
+
+  \item{lambda}{Regularisation coefficient.  Can be a
+  single value or a vector.}
+
+  \item{...}{Passed to \code{\link[RevoScaleR]{rxCovCor}}}
+}
+\description{
+Fits ridge regression model using the correlation matrix.  Supports estimation of multiple values of the regularisation coefficient (lambda).
+}
+\author{
+Derek McRae Norton
+}
+\references{
+http://blog.revolutionanalytics.com/2014/03/extending-revoscaler-ridge-regression.html
+}
+