Cbind result of aplucter to dataframe in R
I perform cluster analysis and i must use apcluster library
library(apcluster)
## create four synthetic 2D clusters
cl1 <- cbind(rnorm(30, 0.3, 0.05), rnorm(30, 0.7, 0.04))
cl2 <- cbind(rnorm(30, 0.7, 0.04), rnorm(30, 0.4, .05))
cl3 <- cbind(rnorm(20, 0.50, 0.03), rnorm(20, 0.72, 0.03))
cl4 <- cbind(rnorm(25, 0.50, 0.03), rnorm(25, 0.42, 0.04))
x <- rbind(cl1, cl2, cl3, cl4)
## run apcluster() (you may replace the Euclidean distance by a different
## distance, e.g. driving distance, driving time)
apres <- apcluster(negDistMat(r=2), x, q=0)
After the clustering, selected cluster i want to join to x data.frame to see
observation and what it cluster.
I did so
cbind(x, mycluster=apres$Clusters)
and error
Error in apres$Clusters : $ operator not defined for this S4 class
How should i do?
[,1] [,2] cluster
[1,] 0.3671142 0.6204475 2
r dataframe
asked Nov 17 '18 at 10:03
d-maxd-max
728
add a comment |
I perform cluster analysis and i must use apcluster library
library(apcluster)
## create four synthetic 2D clusters
cl1 <- cbind(rnorm(30, 0.3, 0.05), rnorm(30, 0.7, 0.04))
cl2 <- cbind(rnorm(30, 0.7, 0.04), rnorm(30, 0.4, .05))
cl3 <- cbind(rnorm(20, 0.50, 0.03), rnorm(20, 0.72, 0.03))
cl4 <- cbind(rnorm(25, 0.50, 0.03), rnorm(25, 0.42, 0.04))
x <- rbind(cl1, cl2, cl3, cl4)
## run apcluster() (you may replace the Euclidean distance by a different
## distance, e.g. driving distance, driving time)
apres <- apcluster(negDistMat(r=2), x, q=0)
After the clustering, selected cluster i want to join to x data.frame to see
observation and what it cluster.
I did so
cbind(x, mycluster=apres$Clusters)
and error
Error in apres$Clusters : $ operator not defined for this S4 class
How should i do?
[,1] [,2] cluster
[1,] 0.3671142 0.6204475 2
r dataframe
asked Nov 17 '18 at 10:03
d-maxd-max
728
add a comment |
I perform cluster analysis and i must use apcluster library
library(apcluster)
## create four synthetic 2D clusters
cl1 <- cbind(rnorm(30, 0.3, 0.05), rnorm(30, 0.7, 0.04))
cl2 <- cbind(rnorm(30, 0.7, 0.04), rnorm(30, 0.4, .05))
cl3 <- cbind(rnorm(20, 0.50, 0.03), rnorm(20, 0.72, 0.03))
cl4 <- cbind(rnorm(25, 0.50, 0.03), rnorm(25, 0.42, 0.04))
x <- rbind(cl1, cl2, cl3, cl4)
## run apcluster() (you may replace the Euclidean distance by a different
## distance, e.g. driving distance, driving time)
apres <- apcluster(negDistMat(r=2), x, q=0)
After the clustering, selected cluster i want to join to x data.frame to see
observation and what it cluster.
I did so
cbind(x, mycluster=apres$Clusters)
and error
Error in apres$Clusters : $ operator not defined for this S4 class
How should i do?
[,1] [,2] cluster
[1,] 0.3671142 0.6204475 2
r dataframe
asked Nov 17 '18 at 10:03
d-maxd-max
728
I perform cluster analysis and i must use apcluster library
library(apcluster)
## create four synthetic 2D clusters
cl1 <- cbind(rnorm(30, 0.3, 0.05), rnorm(30, 0.7, 0.04))
cl2 <- cbind(rnorm(30, 0.7, 0.04), rnorm(30, 0.4, .05))
cl3 <- cbind(rnorm(20, 0.50, 0.03), rnorm(20, 0.72, 0.03))
cl4 <- cbind(rnorm(25, 0.50, 0.03), rnorm(25, 0.42, 0.04))
x <- rbind(cl1, cl2, cl3, cl4)
## run apcluster() (you may replace the Euclidean distance by a different
## distance, e.g. driving distance, driving time)
apres <- apcluster(negDistMat(r=2), x, q=0)
After the clustering, selected cluster i want to join to x data.frame to see
observation and what it cluster.
I did so
cbind(x, mycluster=apres$Clusters)
and error
Error in apres$Clusters : $ operator not defined for this S4 class
How should i do?
[,1] [,2] cluster
[1,] 0.3671142 0.6204475 2
r dataframe
r dataframe
asked Nov 17 '18 at 10:03
d-maxd-max
728
asked Nov 17 '18 at 10:03
d-maxd-max
728
asked Nov 17 '18 at 10:03
d-maxd-max
728
asked Nov 17 '18 at 10:03
d-maxd-max
728
asked Nov 17 '18 at 10:03
d-maxd-max
728
728
add a comment |
add a comment |
1 Answer
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The first issue is that apres isn't an S3 class object and using $ isn't going to work. See apres and you will see @ used in a similar fashion. In particular, as to get the resulting clusters, you want
cls <- apres@clusters
Next thing is that cls is a list of four elements, each elements containing indices of observations belonging to the corresponding cluster. One way then to associate the observation (value) with its cluster (name) would be
clsNm <- sort(setNames(unlist(cls), rep(1:length(cls), times = lengths(cls))))
head(clsNm)
# 1 1 1 1 1 1
# 1 2 3 4 5 6
Then we may do what you tried
head(cbind(x, cluster = as.integer(names(clsNm))), 2)
# cluster
# [1,] 0.2526693 0.6764543 1
# [2,] 0.2781545 0.6774726 1
answered Nov 17 '18 at 10:14
Julius VainoraJulius Vainora
34.7k76079
add a comment |
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1 Answer
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1 Answer
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The first issue is that apres isn't an S3 class object and using $ isn't going to work. See apres and you will see @ used in a similar fashion. In particular, as to get the resulting clusters, you want
cls <- apres@clusters
Next thing is that cls is a list of four elements, each elements containing indices of observations belonging to the corresponding cluster. One way then to associate the observation (value) with its cluster (name) would be
clsNm <- sort(setNames(unlist(cls), rep(1:length(cls), times = lengths(cls))))
head(clsNm)
# 1 1 1 1 1 1
# 1 2 3 4 5 6
Then we may do what you tried
head(cbind(x, cluster = as.integer(names(clsNm))), 2)
# cluster
# [1,] 0.2526693 0.6764543 1
# [2,] 0.2781545 0.6774726 1
answered Nov 17 '18 at 10:14
Julius VainoraJulius Vainora
34.7k76079
add a comment |
The first issue is that apres isn't an S3 class object and using $ isn't going to work. See apres and you will see @ used in a similar fashion. In particular, as to get the resulting clusters, you want
cls <- apres@clusters
Next thing is that cls is a list of four elements, each elements containing indices of observations belonging to the corresponding cluster. One way then to associate the observation (value) with its cluster (name) would be
clsNm <- sort(setNames(unlist(cls), rep(1:length(cls), times = lengths(cls))))
head(clsNm)
# 1 1 1 1 1 1
# 1 2 3 4 5 6
Then we may do what you tried
head(cbind(x, cluster = as.integer(names(clsNm))), 2)
# cluster
# [1,] 0.2526693 0.6764543 1
# [2,] 0.2781545 0.6774726 1
answered Nov 17 '18 at 10:14
Julius VainoraJulius Vainora
34.7k76079
add a comment |
The first issue is that apres isn't an S3 class object and using $ isn't going to work. See apres and you will see @ used in a similar fashion. In particular, as to get the resulting clusters, you want
cls <- apres@clusters
Next thing is that cls is a list of four elements, each elements containing indices of observations belonging to the corresponding cluster. One way then to associate the observation (value) with its cluster (name) would be
clsNm <- sort(setNames(unlist(cls), rep(1:length(cls), times = lengths(cls))))
head(clsNm)
# 1 1 1 1 1 1
# 1 2 3 4 5 6
Then we may do what you tried
head(cbind(x, cluster = as.integer(names(clsNm))), 2)
# cluster
# [1,] 0.2526693 0.6764543 1
# [2,] 0.2781545 0.6774726 1
answered Nov 17 '18 at 10:14
Julius VainoraJulius Vainora
34.7k76079
The first issue is that apres isn't an S3 class object and using $ isn't going to work. See apres and you will see @ used in a similar fashion. In particular, as to get the resulting clusters, you want
cls <- apres@clusters
Next thing is that cls is a list of four elements, each elements containing indices of observations belonging to the corresponding cluster. One way then to associate the observation (value) with its cluster (name) would be
clsNm <- sort(setNames(unlist(cls), rep(1:length(cls), times = lengths(cls))))
head(clsNm)
# 1 1 1 1 1 1
# 1 2 3 4 5 6
Then we may do what you tried
head(cbind(x, cluster = as.integer(names(clsNm))), 2)
# cluster
# [1,] 0.2526693 0.6764543 1
# [2,] 0.2781545 0.6774726 1
answered Nov 17 '18 at 10:14
Julius VainoraJulius Vainora
34.7k76079
answered Nov 17 '18 at 10:14
Julius VainoraJulius Vainora
34.7k76079
answered Nov 17 '18 at 10:14
Julius VainoraJulius Vainora
34.7k76079
answered Nov 17 '18 at 10:14
Julius VainoraJulius Vainora
34.7k76079
34.7k76079
add a comment |
add a comment |
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