From: Benjamin Auder Date: Tue, 15 Jun 2021 05:40:33 +0000 (+0200) Subject: Fix gmodel == tree for regression X-Git-Url: https://git.auder.net/doc/html/css/current/scripts/R.css?a=commitdiff_plain;h=c152ea666f61e36b095bf8b42ab99efe9eab2dba;p=agghoo.git Fix gmodel == tree for regression --- diff --git a/R/R6_AgghooCV.R b/R/R6_AgghooCV.R index c555641..81ddbe1 100644 --- a/R/R6_AgghooCV.R +++ b/R/R6_AgghooCV.R @@ -89,7 +89,7 @@ AgghooCV <- R6::R6Class("AgghooCV", return (invisible(NULL)) } V <- length(private$pmodels) - oneLineX <- as.data.frame(t(as.matrix(X[1,]))) + oneLineX <- t(as.matrix(X[1,])) if (length(private$pmodels[[1]]$model(oneLineX)) >= 2) # Soft classification: return (Reduce("+", lapply(private$pmodels, function(m) m$model(X))) / V) diff --git a/R/R6_Model.R b/R/R6_Model.R index 96f892d..3c84812 100644 --- a/R/R6_Model.R +++ b/R/R6_Model.R @@ -40,7 +40,7 @@ Model <- R6::R6Class("Model", if (is.null(params)) # Here, gmodel is a string (= its family), # because a custom model must be given with its parameters. - params <- as.list(private$getParams(gmodel, data, target)) + params <- as.list(private$getParams(gmodel, data, target, task)) private$params <- params if (is.character(gmodel)) gmodel <- private$getGmodel(gmodel, task) @@ -115,7 +115,7 @@ Model <- R6::R6Class("Model", } }, # Return a default list of parameters, given a gmodel family - getParams = function(family, data, target) { + getParams = function(family, data, target, task) { if (family == "tree") { # Run rpart once to obtain a CV grid for parameter cp require(rpart) @@ -125,13 +125,13 @@ Model <- R6::R6Class("Model", minsplit = 2, minbucket = 1, xval = 0) - r <- rpart(target ~ ., df, method="class", control=ctrl) + method <- ifelse(task == "classification", "class", "anova") + r <- rpart(target ~ ., df, method=method, control=ctrl) cps <- r$cptable[-1,1] - if (length(cps) <= 11) { - if (length(cps == 0)) - stop("No cross-validation possible: select another model") + if (length(cps) <= 1) + stop("No cross-validation possible: select another model") + if (length(cps) <= 11) return (cps) - } step <- (length(cps) - 1) / 10 cps[unique(round(seq(1, length(cps), step)))] }