122 lines
4.2 KiB
R
122 lines
4.2 KiB
R
# PREDICTION --------------------------------------------------------------
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# LES METHODES SUIVANTES PERMETTENT DE PREDIRE LA PROBA D'INTERET POUR
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# LES TROIS CLASSES SUIVANTES : train, randomForest, RandomForest{party}
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#' VT.predict generic function
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#'
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#' @param rfor random forest model. Can be train, randomForest or RandomForest
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#' class.
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#' @param newdata Newdata to predict by the random forest model. If missing, OOB
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#' predictions are returned.
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#' @param type Must be binary or continous, depending on the outcome. Only
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#' binary is really available.
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#'
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#' @return vector \eqn{E(Y=1)}
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#'
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#'
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#' @include setClass.R
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#' @importClassesFrom party RandomForest
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#'
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#' @name VT.predict
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#'
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setGeneric("VT.predict",
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function(rfor, newdata, type){standardGeneric("VT.predict")}
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)
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#' @describeIn VT.predict rfor(RandomForest) newdata (missing) type (character)
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setMethod(
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f = "VT.predict",
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signature = c(rfor = "RandomForest", newdata = "missing", type = "character"),
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function(rfor, type = "binary"){
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if(! type %in% c("binary", "continous")) stop("Type must be Binary or continous")
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if(type == "binary"){
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if(!requireNamespace("party", quietly = TRUE)) stop("Party package must be loaded.")
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tmp <- stats::predict(rfor, OOB = T, type = "prob")
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tmp <- unlist(tmp)
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tmp <- tmp[seq(2, length(tmp), 2)]
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}else{
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message("continous is not done yet")
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tmp <- NULL
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}
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return(tmp)
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}
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)
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#' @describeIn VT.predict rfor(RandomForest) newdata (data.frame) type (character)
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setMethod(
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f = "VT.predict",
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signature = c(rfor = "RandomForest", newdata = "data.frame", type = "character"),
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function(rfor, newdata, type = "binary"){
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if(! type %in% c("binary", "continous")) stop("Type must be Binary or continous")
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if(type == "binary"){
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if(!requireNamespace("party", quietly = TRUE)) stop("Party package must be loaded.")
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tmp <- stats::predict(rfor, newdata = newdata, type = "prob")
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tmp <- unlist(tmp)
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tmp <- tmp[seq(2, length(tmp), 2)]
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}else{
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message("continous is not done yet")
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tmp <- NULL
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}
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return(tmp)
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}
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)
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#' @describeIn VT.predict rfor(randomForest) newdata (missing) type (character)
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setMethod(
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f = "VT.predict",
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signature = c(rfor = "randomForest", newdata = "missing", type = "character"),
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function(rfor, type = "binary"){
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if(! type %in% c("binary", "continous")) stop("Type must be Binary or continous")
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if(type == "binary"){
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# no longer available in all version ?!
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# tmp <- rfor$vote[, 2] # get the "o" prob
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if(!requireNamespace("randomForest", quietly = TRUE)) stop("randomForest package must be loaded.")
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tmp <- stats::predict(rfor, type = "prob")[, 2] # We want to get the "o" prob
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}else{
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message("continous is not done yet")
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tmp <- NULL
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}
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return(tmp)
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}
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)
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#' @describeIn VT.predict rfor(randomForest) newdata (data.frame) type (character)
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setMethod(
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f = "VT.predict",
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signature = c(rfor = "randomForest", newdata = "data.frame", type = "character"),
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function(rfor, newdata, type = "binary"){
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if(! type %in% c("binary", "continous")) stop("Type must be Binary or continous")
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if(type == "binary"){
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if(!requireNamespace("randomForest", quietly = TRUE)) stop("randomForest package must be loaded.")
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tmp <- stats::predict(rfor, newdata = newdata, type = "prob")[, 2] # We want to get the "o" prob
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}else{
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message("continous is not done yet")
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tmp <- NULL
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}
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return(tmp)
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}
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)
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#' @describeIn VT.predict rfor(train) newdata (ANY) type (character)
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setMethod(
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f = "VT.predict",
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signature = c(rfor = "train", newdata = "ANY", type = "character"),
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function(rfor, newdata, type = "binary"){
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if(!requireNamespace("caret", quietly = TRUE)) stop("caret package must be loaded.")
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return(VT.predict(rfor$finalModel, newdata, type))
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}
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)
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#' @describeIn VT.predict rfor(train) newdata (missing) type (character)
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setMethod(
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f = "VT.predict",
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signature = c(rfor = "train", newdata = "missing", type = "character"),
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function(rfor, type = "binary"){
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if(!requireNamespace("caret", quietly = TRUE)) stop("caret package must be loaded.")
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return(VT.predict(rfor=rfor$finalModel, type=type))
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}
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) |