This is my vector before kmeans -
这是kmeans -之前的向量
> sort(table(mydata))
mydata
23 7 9 4 10 3 5 8 2 1
1 3 3 4 5 6 6 6 7 9
km <- kmeans(mydata, centers = 10)
After kmeans -
后kmeans -
> sort(table(km$cluster))
km$cluster
1 6 7 3 5 2 4 10 8 9
1 3 3 4 5 6 6 6 7 9
Clearly, all my 1s are stored in cluster 9, all 2s are stored in Cluster 8 and so on.
显然，所有的1s都存储在集群9中，所有的2s都存储在集群8中等等。
Can I find using R which cluster a particular number belongs to? Say, finding which cluster my 1s are in?
我能用R找到一个特定的数属于哪个簇吗?比如说，找到我的1s星系团在哪?
1 个解决方案
#1
4
The values for $cluster are returned in the same order as your original data.
$cluster的值以与原始数据相同的顺序返回。
mydata <- rep(c(23,7,9,4,10,3,5,8,2,1), c(1,3,3,4,5,6,6,6,7,9))
sort(table(mydata))
# mydata
# 23 7 9 4 10 3 5 8 2 1
# 1 3 3 4 5 6 6 6 7 9
km <- kmeans(mydata, centers = 10)
unique(cbind(value=mydata, clust=km$cluster))
# value clust
# [1,] 23 9
# [2,] 7 5
# [3,] 9 7
# [4,] 4 4
# [5,] 10 1
# [6,] 3 10
# [7,] 5 2
# [8,] 8 8
# [9,] 2 6
# [10,] 1 3
Here i've just re-joined the two with cbind and used unique to eliminate all the dups since you have such discrete data.
这里，我用cbind重新加入了这两个函数，并使用unique来消除所有dup，因为您有如此离散的数据。
#1
4
The values for $cluster are returned in the same order as your original data.
$cluster的值以与原始数据相同的顺序返回。
mydata <- rep(c(23,7,9,4,10,3,5,8,2,1), c(1,3,3,4,5,6,6,6,7,9))
sort(table(mydata))
# mydata
# 23 7 9 4 10 3 5 8 2 1
# 1 3 3 4 5 6 6 6 7 9
km <- kmeans(mydata, centers = 10)
unique(cbind(value=mydata, clust=km$cluster))
# value clust
# [1,] 23 9
# [2,] 7 5
# [3,] 9 7
# [4,] 4 4
# [5,] 10 1
# [6,] 3 10
# [7,] 5 2
# [8,] 8 8
# [9,] 2 6
# [10,] 1 3
Here i've just re-joined the two with cbind and used unique to eliminate all the dups since you have such discrete data.
这里，我用cbind重新加入了这两个函数，并使用unique来消除所有dup，因为您有如此离散的数据。