R中的SVM-RFE算法的實現

我使用R代碼來實現SVM-RFE算法從這個源http://www.uccor.edu.ar/paginas/seminarios/Software/SVM_RFE_R_implementation.pdf但我做了一個小的修改，使r代碼使用gnum庫。該代碼是下面的：R中的SVM-RFE算法的實現

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) 
}

該功能接收matrix作爲input用於x和factor作爲input爲y。我使用的功能對於一些數據，我收到的最後一個迭代以下錯誤信息：

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

調試代碼，我得到這個：

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)

那麼，有什麼功能的錯誤？

來源

2016-08-11 CreamStat

看起來像只有一個功能保留時，矩陣轉換爲列表。試試這個：

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

來源

2016-08-11 10:17:59 dratewka

R中的SVM-RFE算法的實現

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