r - knn 函数出错

Question

我尝试运行这条线:

knn(mydades.training[,-7],mydades.test[,-7],mydades.training[,7],k=5)

但我总是收到这个错误:

Error in knn(mydades.training[, -7], mydades.test[, -7], mydades.training[,  : 
  NA/NaN/Inf in foreign function call (arg 6)
In addition: Warning messages:
1: In knn(mydades.training[, -7], mydades.test[, -7], mydades.training[,  :
  NAs introduced by coercion
2: In knn(mydades.training[, -7], mydades.test[, -7], mydades.training[,  :
  NAs introduced by coercion

有什么想法吗？

PS:mydades.training 和 mydades.test 定义如下:

N <- nrow(mydades) 
permut <- sample(c(1:N),N,replace=FALSE)
ord <- order(permut)
mydades.shuffled <- mydades[ord,]
prop.train <- 1/3
NOMBRE <- round(prop.train*N)
mydades.training <- mydades.shuffled[1:NOMBRE,]
mydades.test <- mydades.shuffled[(NOMBRE+1):N,]

Answer 1

我怀疑您的问题在于“mydades”中有非数字数据字段。错误行:

NA/NaN/Inf in foreign function call (arg 6)

让我怀疑对 C 语言实现的 knn 函数调用失败了。 R 中的许多函数实际上调用底层的、更高效的 C 实现，而不是仅在 R 中实现算法。如果您在 R 控制台中只键入“knn”，则可以检查“knn”的 R 实现。存在以下行:

 Z <- .C(VR_knn, as.integer(k), as.integer(l), as.integer(ntr), 
        as.integer(nte), as.integer(p), as.double(train), as.integer(unclass(clf)), 
        as.double(test), res = integer(nte), pr = double(nte), 
        integer(nc + 1), as.integer(nc), as.integer(FALSE), as.integer(use.all))

其中 .C 表示我们正在使用提供的函数参数调用名为“VR_knn”的 C 函数。因为你有两个错误

NAs introduced by coercion

我认为两个 as.double/as.integer 调用失败，并引入 NA 值。如果我们开始计算参数，第 6 个参数是:

as.double(train)

在以下情况下可能会失败:

# as.double can not translate text fields to doubles, they are coerced to NA-values:
> as.double("sometext")
[1] NA
Warning message:
NAs introduced by coercion
# while the following text is cast to double without an error:
> as.double("1.23")
[1] 1.23

你会得到两个强制错误，它们可能是由 'as.double(train)' 和 'as.double(test)' 给出的。由于您没有向我们提供“mydades”的确切细节，以下是我的一些最佳猜测(以及人工多元正态分布数据):

library(MASS)
mydades <- mvrnorm(100, mu=c(1:6), Sigma=matrix(1:36, ncol=6))
mydades <- cbind(mydades, sample(LETTERS[1:5], 100, replace=TRUE))

# This breaks knn
mydades[3,4] <- Inf
# This breaks knn
mydades[4,3] <- -Inf
# These, however, do not introduce the coercion for NA-values error message

# This breaks knn and gives the same error; just some raw text
mydades[1,2] <- mydades[50,1] <- "foo"
mydades[100,3] <- "bar"

# ... or perhaps wrongly formatted exponential numbers?
mydades[1,1] <- "2.34EXP-05"

# ... or wrong decimal symbol?
mydades[3,3] <- "1,23" 
# should be 1.23, as R uses '.' as decimal symbol and not ','

# ... or most likely a whole column is non-numeric, since the error is given twice (as.double problem both in training AND test set)
mydades[,1] <- sample(letters[1:5],100,replace=TRUE)

我不会将数字数据和类标签都保存在一个矩阵中，也许您可​​以将数据拆分为:

mydadesnumeric <- mydades[,1:6] # 6 first columns
mydadesclasses <- mydades[,7]

使用调用

str(mydades); summary(mydades)

还可以帮助您/我们找到有问题的数据条目并将其更正为数字条目或省略非数字字段。

其余的运行代码(在破坏数据之后)，由您提供:

N <- nrow(mydades) 
permut <- sample(c(1:N),N,replace=FALSE)
ord <- order(permut)
mydades.shuffled <- mydades[ord,]
prop.train <- 1/3
NOMBRE <- round(prop.train*N)
mydades.training <- mydades.shuffled[1:NOMBRE,]
mydades.test <- mydades.shuffled[(NOMBRE+1):N,]

# 7th column seems to be the class labels
knn(train=mydades.training[,-7],test=mydades.test[,-7],mydades.training[,7],k=5)