[aggexp.git] / pkg / R / m_SVMclassif.R

#' @include b_Algorithm.R

#' @title SVM Algorithm
#'
#' @description SVM classifier.
#' Inherits \code{\link{Algorithm}}
#'
#' @field kernel TODO
#' @field someParam TODO
#'
SVMclassif = setRefClass(
	Class = "SVMclassif",

	fields = c(
		kernel = "numeric",
		someParam = "logical"
	),

	contains = "Algorithm",

	methods = list(
		initialize = function(...)
		{
			callSuper(...)
			#TODO
		},
		predict_noNA = function(XY, x)
		{
			if (nrow(XY) <= 5)
				return (10) #TODO

			require(kernlab, quietly=TRUE)
			XY[,"alert"] = XY[,"Measure"] > 30
			alertsIndices = XY[,"alert"]
			XY[alertsIndices,"alert"] = "alert"
			XY[!alertsIndices,"alert"] = "noalert"
			XY[,"alert"] = as.factor(XY[,"alert"])
			XY[,"Measure"] = NULL

			ks = ksvm(alert ~ ., data=XY)
			pred = as.character(predict(ks, as.data.frame(x)))
			pred[pred == "alert"] = 70
			pred[pred == "noalert"] = 10
			return (as.numeric(pred))
		}
	)
)
Commit	Line	Data
	1	#' @include b_Algorithm.R
	2
	3	#' @title SVM Algorithm
	4	#'
	5	#' @description SVM classifier.
	6	#' Inherits \code{\link{Algorithm}}
	7	#'
	8	#' @field kernel TODO
	9	#' @field someParam TODO
	10	#'
	11	SVMclassif = setRefClass(
	12	Class = "SVMclassif",
	13
	14	fields = c(
	15	kernel = "numeric",
	16	someParam = "logical"
	17	),
	18
	19	contains = "Algorithm",
	20
	21	methods = list(
	22	initialize = function(...)
	23	{
	24	callSuper(...)
	25	#TODO
	26	},
	27	predict_noNA = function(XY, x)
	28	{
	29	if (nrow(XY) <= 5)
	30	return (10) #TODO
	31
	32	require(kernlab, quietly=TRUE)
	33	XY[,"alert"] = XY[,"Measure"] > 30
	34	alertsIndices = XY[,"alert"]
	35	XY[alertsIndices,"alert"] = "alert"
	36	XY[!alertsIndices,"alert"] = "noalert"
	37	XY[,"alert"] = as.factor(XY[,"alert"])
	38	XY[,"Measure"] = NULL
	39
	40	ks = ksvm(alert ~ ., data=XY)
	41	pred = as.character(predict(ks, as.data.frame(x)))
	42	pred[pred == "alert"] = 70
	43	pred[pred == "noalert"] = 10
	44	return (as.numeric(pred))
	45	}
	46	)
	47	)