75 lines
3.1 KiB
R
75 lines
3.1 KiB
R
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#' Load Random Forest
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#'
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#' Loads a random forest that was saved using \code{\link{save_forest}}.
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#'
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#' @param forest The directory created that saved the previous forest.
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#' @return A JForest object; see \code{\link{train}} for details.
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#' @export
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#' @seealso \code{\link{train}}, \code{\link{save_forest}}
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#' @examples
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#' # Regression Example
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#' x1 <- rnorm(1000)
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#' x2 <- rnorm(1000)
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#' y <- 1 + x1 + x2 + rnorm(1000)
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#'
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#' data <- data.frame(x1, x2, y)
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#' forest <- train(y ~ x1 + x2, data,
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#' ntree=100, numberOfSplits = 5, mtry = 1, nodeSize = 5)
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#'
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#' save_forest(forest, "trees")
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#' new_forest <- load_forest("trees")
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load_forest <- function(directory){
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# First load the response combiners and the split finders
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nodeResponseCombiner.java <- .jcall(.class_DataUtils, makeResponse(.class_Object), "loadObject", paste0(directory, "/nodeResponseCombiner.jData"))
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nodeResponseCombiner.java <- .jcast(nodeResponseCombiner.java, .class_ResponseCombiner)
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splitFinder.java <- .jcall(.class_DataUtils, makeResponse(.class_Object), "loadObject", paste0(directory, "/splitFinder.jData"))
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splitFinder.java <- .jcast(splitFinder.java, .class_SplitFinder)
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forestResponseCombiner.java <- .jcall(.class_DataUtils, makeResponse(.class_Object), "loadObject", paste0(directory, "/forestResponseCombiner.jData"))
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forestResponseCombiner.java <- .jcast(forestResponseCombiner.java, .class_ResponseCombiner)
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covariateList <- .jcall(.class_DataUtils, makeResponse(.class_Object), "loadObject", paste0(directory, "/covariateList.jData"))
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covariateList <- .jcast(covariateList, .class_List)
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params <- readRDS(paste0(directory, "/parameters.rData"))
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call <- readRDS(paste0(directory, "/call.rData"))
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params$nodeResponseCombiner$javaObject <- nodeResponseCombiner.java
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params$splitFinder$javaObject <- splitFinder.java
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params$forestResponseCombiner$javaObject <- forestResponseCombiner.java
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forest <- load_forest_args_provided(directory, params$nodeResponseCombiner, params$splitFinder, params$forestResponseCombiner, covariateList, call,
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params$ntree, params$numberOfSplits, params$mtry, params$nodeSize, params$maxNodeDepth, params$splitPureNodes)
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return(forest)
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}
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#' @export
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load_forest_args_provided <- function(treeDirectory, nodeResponseCombiner, splitFinder, forestResponseCombiner,
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covariateList.java, call, ntree, numberOfSplits, mtry, nodeSize, maxNodeDepth = 100000, splitPureNodes=TRUE){
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params <- list(
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splitFinder=splitFinder,
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nodeResponseCombiner=nodeResponseCombiner,
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forestResponseCombiner=forestResponseCombiner,
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ntree=ntree,
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numberOfSplits=numberOfSplits,
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mtry=mtry,
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nodeSize=nodeSize,
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splitPureNodes=splitPureNodes,
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maxNodeDepth = maxNodeDepth
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)
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forest.java <- .jcall(.class_DataUtils, makeResponse(.class_Forest), "loadForest", treeDirectory, forestResponseCombiner$javaObject)
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forestObject <- list(call=call, javaObject=forest.java, covariateList=covariateList.java, params=params)
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class(forestObject) <- "JRandomForest"
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return(forestObject)
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}
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