在R中SVM出错

Question

在R中SVM出错

3

我是R语言新手，尝试从文本中检索数据，然后将其应用于支持向量机（SVM）进行分类。以下是代码：

train<-read.table("training.txt")
train[which(train=="?",arr.ind=TRUE)]<-NA
train=unique(train)
y=train[,length(train)]

classifier<-svm(y~.,data=train[,-length(train)],scale=F)
classifier<-svm(x=train[,-length(train)],y=factor(y),scale=F)

我尝试两种不同的方式调用svm，对于第一种方式 (svm(y~.,data=train[,-length(train)],scale=F)) 看起来是可以的，但是第二种方式有问题，它报告了：

Error in svm.default(x = train[, length(train)], y = factor(y), scale = F) : 
  NA/NaN/Inf in foreign function call (arg 1)
In addition: Warning message:
In svm.default(x = train[, length(train)], y = factor(y), scale = F) :
  NAs introduced by coercion

这里是一个 training.txt 的样本，最后一列是目标。

39,State-gov,77516,Bachelors,13,Never-married,Adm-clerical,Not-in-family,White,Male,2174,0,40,United-States,0
50,Self-emp-not-inc,83311,Bachelors,13,Married-civ-spouse,Exec-managerial,Husband,White,Male,0,0,13,United-States,0
38,Private,215646,HS-grad,9,Divorced,Handlers-cleaners,Not-in-family,White,Male,0,0,40,United-States,0
53,Private,234721,11th,7,Married-civ-spouse,Handlers-cleaners,Husband,Black,Male,0,0,40,United-States,0
28,Private,338409,Bachelors,13,Married-civ-spouse,Prof-specialty,Wife,Black,Female,0,0,40,Cuba,0
37,Private,284582,Masters,14,Married-civ-spouse,Exec-managerial,Wife,White,Female,0,0,40,United-States,0
49,Private,160187,9th,5,Married-spouse-absent,Other-service,Not-in-family,Black,Female,0,0,16,Jamaica,0
52,Self-emp-not-inc,209642,HS-grad,9,Married-civ-spouse,Exec-managerial,Husband,White,Male,0,0,45,United-States,1
31,Private,45781,Masters,14,Never-married,Prof-specialty,Not-in-family,White,Female,14084,0,50,United-States,1
42,Private,159449,Bachelors,13,Married-civ-spouse,Exec-managerial,Husband,White,Male,5178,0,40,United-States,1
37,Private,280464,Some-college,10,Married-civ-spouse,Exec-managerial,Husband,Black,Male,0,0,80,United-States,1
30,State-gov,141297,Bachelors,13,Married-civ-spouse,Prof-specialty,Husband,Asian-Pac-Islander,Male,0,0,40,India,1
23,Private,122272,Bachelors,13,Never-married,Adm-clerical,Own-child,White,Female,0,0,30,United-States,0
32,Private,205019,Assoc-acdm,12,Never-married,Sales,Not-in-family,Black,Male,0,0,50,United-States,0
40,Private,121772,Assoc-voc,11,Married-civ-spouse,Craft-repair,Husband,Asian-Pac-Islander,Male,0,0,40,NA,1

有什么想法吗？提前感谢！

- Lei

1个回答

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可以查看英文原文，
原文链接

- LyzandeR · Accepted Answer

文档说明：

x 参数：

a data matrix, a vector, or a sparse matrix (object of class Matrix
provided by the Matrix package,or of class matrix.csr provided by the
SparseM package, or of class simple_triplet_matrix provided by the slam package).

对于y参数：

a response vector with one label for each row/component of x. Can be
either a factor (for classification tasks) or a numeric vector (for regression).

当您键入第二个函数中的x=train [,-length(train)]时，实际上使用的是不受支持的data.frame，会导致程序崩溃。 svm函数仅适用于数值矩阵。

library(e1071)
train[which(train=="?",arr.ind=TRUE)]<-NA
train=unique(train)
y=factor(train[,length(train)])
train <- data.frame(lapply(train,as.numeric)) #convert to numeric. factors are integer fields anyway behind the scenes.

train <- as.matrix(train[-length(train)])

classifier<-svm(x= train ,y=y,scale=F)

输出：

> summary(classifier)

Call:
svm.default(x = train, y = y, scale = F)


Parameters:
   SVM-Type:  C-classification 
 SVM-Kernel:  radial 
       cost:  1 
      gamma:  0.07142857 

Number of Support Vectors:  14

 ( 9 5 )


Number of Classes:  2 

Levels: 
 0 1