seq.default(from = min(x，na.rm = TRUE)，to = max(x，na.rm = TRUE)，中的错误:'from'不能为NA，NaN或无限 [英] Error in seq.default(from = min(x, na.rm = TRUE), to = max(x, na.rm = TRUE), : 'from' cannot be NA, NaN or infinite

问题描述

我在Knime中使用R Learner.我想离散化一个矩阵，如下所示:

I'm using R Learner in Knime. I want to discretize a matrix, which is the following:

> my_matrix= as(knime.in,"matrix");
> dput(head(my_matrix, 5))
structure(c("KS", "OH", "NJ", "OH", "OK", "128", "107", "137", 
" 84", " 75", "415", "415", "415", "408", "415", "No", "No", 
"No", "Yes", "Yes", "Yes", "Yes", "No", "No", "No", "25", "26", 
" 0", " 0", " 0", "265.1", "161.6", "243.4", "299.4", "166.7", 
"110", "123", "114", " 71", "113", "45.07", "27.47", "41.38", 
"50.90", "28.34", "197.4", "195.5", "121.2", " 61.9", "148.3", 
" 99", "103", "110", " 88", "122", "16.78", "16.62", "10.30", 
" 5.26", "12.61", "244.7", "254.4", "162.6", "196.9", "186.9", 
" 91", "103", "104", " 89", "121", "11.01", "11.45", " 7.32", 
" 8.86", " 8.41", "10.0", "13.7", "12.2", " 6.6", "10.1", " 3", 
" 3", " 5", " 7", " 3", "2.70", "3.70", "3.29", "1.78", "2.73", 
"1", "1", "0", "2", "3", "False", "False", "False", "False", 
"False"), .Dim = c(5L, 20L), .Dimnames = list(c("Row0", "Row1", 
"Row2", "Row3", "Row4"), c("State", "Account length", "Area code", 
"International plan", "Voice mail plan", "Number vmail messages", 
"Total day minutes", "Total day calls", "Total day charge", "Total eve minutes", 
"Total eve calls", "Total eve charge", "Total night minutes", 
"Total night calls", "Total night charge", "Total intl minutes", 
"Total intl calls", "Total intl charge", "Customer service calls", 
"Churn")))

我正在使用以下代码离散化矩阵:

I'm using the following code to discretize the matrix:

require(arules)
#require(arulesViz)
my_matrix= as(knime.in,"matrix");
my_rows= nrow(my_matrix);
my_cols= ncol(my_matrix);
#discretize(x, method="interval", categories = 3, labels = NULL,     
#  ordered=FALSE, onlycuts=FALSE, ...)
typeof(my_matrix)
vector = my_matrix[,2]
my_matrix[,2] = discretize(vector, method="interval", categories = 3, labels=c("length0","length1","length2"))
my_matrix[,3] = ...
etc...

与代码行对应:

my_matrix[,2] = discretize(vector, method="interval", categories = 3, labels=c("length0","length1","length2"))

我收到以下错误:

seq.default(from = min(x，na.rm = TRUE)，to = max(x，na.rm = TRUE)，中的错误:'from'不能为NA，NaN或无限

Error in seq.default(from = min(x, na.rm = TRUE), to = max(x, na.rm = TRUE), : 'from' cannot be NA, NaN or infinite

如果我在此处输入"sum(is.na(vector)):

If I put "sum(is.na(vector)) here:

vector = my_matrix[,2]
sum(is.na(vector))
my_matrix[,2] = discretize(vector, method="interval", categories = 3, labels=c("length0","length1","length2"))

我得到:

> sum(is.na(vector))
[1] 0

所以向量中没有NA元素.无论如何，typeof(matrix)是字符".如果打印矢量，则会得到以下信息:

so I have no NA element in the vector. Anyway, typeof(matrix) is "character". If I print the vector, I get the following:

> vector = my_matrix[,2]
> sum(is.na(vector))
[1] 0
> head(vector, 20)
 Row0  Row1  Row2  Row3  Row4  Row5  Row6  Row7  Row8  Row9 Row10 Row11 Row12 
"128" "107" "137" " 84" " 75" "118" "121" "147" "117" "141" " 65" " 74" "168" 
Row13 Row14 Row15 Row16 Row17 Row18 Row19 
" 95" " 62" "161" " 85" " 93" " 76" " 73" 

推荐答案

问题是您的向量由字符串组成.理想情况下，您可以用knime解决此问题.确实存在进行此类转换的节点.

The problem is that you vector consists of strings. Ideally you solve this problem in knime. Nodes for this kind of conversions do exist.

但是您也可以替换

vector = my_matrix[,2]

通过

vector = as.numeric(my_matrix[,2])

这篇关于seq.default(from = min(x，na.rm = TRUE)，to = max(x，na.rm = TRUE)，中的错误:'from'不能为NA，NaN或无限的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！