pkg/R/m_SVMclassif.R

   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 )