r - SVM-RFE算法在R中的实现

我正在使用R代码从此源http://www.uccor.edu.ar/paginas/seminarios/Software/SVM_RFE_R_implementation.pdf实现SVM-RFE算法，但是我做了一些小的修改，以便r代码使用gnum库。代码如下：

svmrfeFeatureRanking = function(x,y){
  n = ncol(x)

  survivingFeaturesIndexes = seq(1:n)
  featureRankedList = vector(length=n)
  rankedFeatureIndex = n

  while(length(survivingFeaturesIndexes)>0){
    #train the support vector machine
    svmModel = SVM(x[, survivingFeaturesIndexes], y, C = 10, cache_size=500,kernel="linear" )



    #compute ranking criteria
    rankingCriteria = svmModel$w * svmModel$w

    #rank the features
    ranking = sort(rankingCriteria, index.return = TRUE)$ix

    #update feature ranked list
    featureRankedList[rankedFeatureIndex] = survivingFeaturesIndexes[ranking[1]]
    rankedFeatureIndex = rankedFeatureIndex - 1

    #eliminate the feature with smallest ranking criterion
    (survivingFeaturesIndexes = survivingFeaturesIndexes[-ranking[1]])

  }

  return (featureRankedList)
}

该函数将matrix用作input的x，将factor用作input的y。我将函数用于一些数据，并且在上一次迭代中收到以下错误消息：

 Error in if (nrow(x) != length(y)) { : argument is of length zero

调试代码，我得到了：

3 SVM.default(x[, survivingFeaturesIndexes], y, C = 10, cache_size = 500,
    kernel = "linear")
2 SVM(x[, survivingFeaturesIndexes], y, C = 10, cache_size = 500,
    kernel = "linear")
1 svmrfeFeatureRanking(sdatx, ym)

那么，该函数有什么错误呢？

最佳答案

当仅保留一个功能时，矩阵似乎转换为列表。尝试这个：

svmModel = SVM(as.matrix(x[, survivingFeaturesIndexes]), y, C = 10, cache_size=500,kernel="linear" )