How to solve error: "Error in storage.mode(x) <- "double" : 'list' object cannot be coerced to type 'double'" and get results
How to solve error: "Error in storage.mode(x) <- "double" : 'list' object cannot be coerced to type 'double'" and get results
我正在尝试 运行 一些和 k 表示分析。但是我无法解决，因为有一个错误代码。
Error in storage.mode(x) <- "double" : 'list' object cannot be coerced to type 'double'
library(kohonen)
cdata <- read.delim("Cluster.txt", stringsAsFactors=FALSE)
cdata.n <- scale(subset(cdata, select=-c(ID)))
som_model2 <- supersom(data = cdata.n, grid = somgrid(10, 10, "rectangular"))
k = 6
somClusters <- kmeans(som_model2$codes, centers = 6)
建议我使用unlist，结果如下
Cluster means:
[,1]
1 -0.6702128
2 5.2157179
3 1.2555768
4 -0.2632253
5 2.6067733
6 0.3503127
但是例子的结果如下
## Cluster means:
## MONEY VISIT CROSS API
## 1 8.2237320 4.8942046 3.6120212 -0.8606384
## 2 -0.2699493 -0.3223770 -0.3357094 -0.2496793
## 3 0.3566740 0.5408914 0.9180064 -0.6252556
## 4 -0.4596952 -0.6586599 -0.9624127 4.2828612
## 5 2.0625665 2.6264913 2.0452184 -0.7848548
## 6 -0.4199132 -0.5746073 -0.7785007 1.1355674
我怎样才能得到这个结果？
我使用这个数据：
您应该将对象强制转换为矩阵或数据框。
来自 kmeans() 文档：
x = numeric matrix of data, or an object that can be coerced to
such a matrix (such as a numeric vector or a data frame with
all numeric columns)
somClusters2 <- kmeans(data.frame(som_model2$codes), centers = 6)
somClusters2
K-means clustering with 6 clusters of sizes 14, 42, 11, 3, 3, 27
Cluster means:
MONEY VISIT CROSS API
1 -0.4217639 -0.5810061 -0.8014610 1.1764434
2 -0.3080303 -0.3977217 -0.4555428 -0.1649521
3 1.1239411 1.6704112 1.6129638 -0.7312019
4 -0.4606414 -0.6480549 -0.9548480 3.5595079
5 5.1169992 3.9174431 2.7584212 -0.8306366
6 0.1443774 0.2317915 0.5778101 -0.5416495
我正在尝试 运行 一些和 k 表示分析。但是我无法解决，因为有一个错误代码。
Error in storage.mode(x) <- "double" : 'list' object cannot be coerced to type 'double'
library(kohonen)
cdata <- read.delim("Cluster.txt", stringsAsFactors=FALSE)
cdata.n <- scale(subset(cdata, select=-c(ID)))
som_model2 <- supersom(data = cdata.n, grid = somgrid(10, 10, "rectangular"))
k = 6
somClusters <- kmeans(som_model2$codes, centers = 6)
建议我使用unlist，结果如下
Cluster means:
[,1]
1 -0.6702128
2 5.2157179
3 1.2555768
4 -0.2632253
5 2.6067733
6 0.3503127
但是例子的结果如下
## Cluster means:
## MONEY VISIT CROSS API
## 1 8.2237320 4.8942046 3.6120212 -0.8606384
## 2 -0.2699493 -0.3223770 -0.3357094 -0.2496793
## 3 0.3566740 0.5408914 0.9180064 -0.6252556
## 4 -0.4596952 -0.6586599 -0.9624127 4.2828612
## 5 2.0625665 2.6264913 2.0452184 -0.7848548
## 6 -0.4199132 -0.5746073 -0.7785007 1.1355674
我怎样才能得到这个结果？
我使用这个数据：
您应该将对象强制转换为矩阵或数据框。
来自 kmeans() 文档：
x = numeric matrix of data, or an object that can be coerced to such a matrix (such as a numeric vector or a data frame with all numeric columns)
somClusters2 <- kmeans(data.frame(som_model2$codes), centers = 6)
somClusters2
K-means clustering with 6 clusters of sizes 14, 42, 11, 3, 3, 27
Cluster means:
MONEY VISIT CROSS API
1 -0.4217639 -0.5810061 -0.8014610 1.1764434
2 -0.3080303 -0.3977217 -0.4555428 -0.1649521
3 1.1239411 1.6704112 1.6129638 -0.7312019
4 -0.4606414 -0.6480549 -0.9548480 3.5595079
5 5.1169992 3.9174431 2.7584212 -0.8306366
6 0.1443774 0.2317915 0.5778101 -0.5416495