我是R的新手，尝试从文本中提取数据，然后在SVM中应用进行分类。这里是代码:
train<-read.table("training.txt")train[which(train=="?",arr.ind=TRUE)]<-NAtrain=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)我尝试了两种不同的方式来调用svm，第一个(svm(y~.,data=train[,-length(train)],scale=F))看起来没问题，但第二个有问题，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这是training.txt的一个样本，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,050,Self-emp-not-inc,83311,Bachelors,13,Married-civ-spouse,Exec-managerial,Husband,White,Male,0,0,13,United-States,038,Private,215646,HS-grad,9,Divorced,Handlers-cleaners,Not-in-family,White,Male,0,0,40,United-States,053,Private,234721,11th,7,Married-civ-spouse,Handlers-cleaners,Husband,Black,Male,0,0,40,United-States,028,Private,338409,Bachelors,13,Married-civ-spouse,Prof-specialty,Wife,Black,Female,0,0,40,Cuba,037,Private,284582,Masters,14,Married-civ-spouse,Exec-managerial,Wife,White,Female,0,0,40,United-States,049,Private,160187,9th,5,Married-spouse-absent,Other-service,Not-in-family,Black,Female,0,0,16,Jamaica,052,Self-emp-not-inc,209642,HS-grad,9,Married-civ-spouse,Exec-managerial,Husband,White,Male,0,0,45,United-States,131,Private,45781,Masters,14,Never-married,Prof-specialty,Not-in-family,White,Female,14084,0,50,United-States,142,Private,159449,Bachelors,13,Married-civ-spouse,Exec-managerial,Husband,White,Male,5178,0,40,United-States,137,Private,280464,Some-college,10,Married-civ-spouse,Exec-managerial,Husband,Black,Male,0,0,80,United-States,130,State-gov,141297,Bachelors,13,Married-civ-spouse,Prof-specialty,Husband,Asian-Pac-Islander,Male,0,0,40,India,123,Private,122272,Bachelors,13,Never-married,Adm-clerical,Own-child,White,Female,0,0,30,United-States,032,Private,205019,Assoc-acdm,12,Never-married,Sales,Not-in-family,Black,Male,0,0,50,United-States,040,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！
回答：
从文档中:
对于x参数:
a data matrix, a vector, or a sparse matrix (object of class Matrixprovided by the Matrix package,or of class matrix.csr provided by theSparseM 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 beeither a factor (for classification tasks) or a numeric vector (for regression).当你在第二个函数中输入x=train[,-length(train)]时，你实际上使用的是一个data.frame，这是不支持的，所以会崩溃。
svm函数仅支持数值矩阵
library(e1071)train[which(train=="?",arr.ind=TRUE)]<-NAtrain=unique(train)y=factor(train[,length(train)])train <- data.frame(lapply(train,as.numeric)) #转换为数值。实际上，分类变量在幕后也是整数字段。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