Which columns are used in kmeans algorithm in R, as there are no arguments for designating columns?
Says, a dataframe df_1 has 8 columns, and following code is used.
res = kmeans(df_1, 4, nstart=40)
The K-means clustering result is stored in res.
In most examples, two dimensions (i.e. two columns) are used to demonstrate the clustering.
However, in the above code, df_1 has 8 dimensions.
How do I know, which columns were used?
r k-means rxkmeans
add a comment |
Says, a dataframe df_1 has 8 columns, and following code is used.
res = kmeans(df_1, 4, nstart=40)
The K-means clustering result is stored in res.
In most examples, two dimensions (i.e. two columns) are used to demonstrate the clustering.
However, in the above code, df_1 has 8 dimensions.
How do I know, which columns were used?
r k-means rxkmeans
have u checked the cheat sheet ?
– sai saran
Nov 16 '18 at 7:36
@sai sara, I did not check any sheet. I just did some research online and no example showed the criteria of the input data.frame.
– Justin
Nov 16 '18 at 7:54
?kmeans can u try this one
– sai saran
Nov 16 '18 at 8:29
1
Description Perform k-means clustering on a data matrix. Usage kmeans(x, centers, iter.max = 10, nstart = 1, algorithm = c("Hartigan-Wong", "Lloyd", "Forgy", "MacQueen"), trace=FALSE) ## S3 method for class 'kmeans' fitted(object, method = c("centers", "classes"), ...)
– sai saran
Nov 16 '18 at 8:30
1
They will all be used. If you want to use only certain columns then limit the columns in the data frame that you pass to the kmeans function
– Cleland
Nov 16 '18 at 9:32
add a comment |
Says, a dataframe df_1 has 8 columns, and following code is used.
res = kmeans(df_1, 4, nstart=40)
The K-means clustering result is stored in res.
In most examples, two dimensions (i.e. two columns) are used to demonstrate the clustering.
However, in the above code, df_1 has 8 dimensions.
How do I know, which columns were used?
r k-means rxkmeans
Says, a dataframe df_1 has 8 columns, and following code is used.
res = kmeans(df_1, 4, nstart=40)
The K-means clustering result is stored in res.
In most examples, two dimensions (i.e. two columns) are used to demonstrate the clustering.
However, in the above code, df_1 has 8 dimensions.
How do I know, which columns were used?
r k-means rxkmeans
r k-means rxkmeans
asked Nov 16 '18 at 7:34
Justin Justin
666
666
have u checked the cheat sheet ?
– sai saran
Nov 16 '18 at 7:36
@sai sara, I did not check any sheet. I just did some research online and no example showed the criteria of the input data.frame.
– Justin
Nov 16 '18 at 7:54
?kmeans can u try this one
– sai saran
Nov 16 '18 at 8:29
1
Description Perform k-means clustering on a data matrix. Usage kmeans(x, centers, iter.max = 10, nstart = 1, algorithm = c("Hartigan-Wong", "Lloyd", "Forgy", "MacQueen"), trace=FALSE) ## S3 method for class 'kmeans' fitted(object, method = c("centers", "classes"), ...)
– sai saran
Nov 16 '18 at 8:30
1
They will all be used. If you want to use only certain columns then limit the columns in the data frame that you pass to the kmeans function
– Cleland
Nov 16 '18 at 9:32
add a comment |
have u checked the cheat sheet ?
– sai saran
Nov 16 '18 at 7:36
@sai sara, I did not check any sheet. I just did some research online and no example showed the criteria of the input data.frame.
– Justin
Nov 16 '18 at 7:54
?kmeans can u try this one
– sai saran
Nov 16 '18 at 8:29
1
Description Perform k-means clustering on a data matrix. Usage kmeans(x, centers, iter.max = 10, nstart = 1, algorithm = c("Hartigan-Wong", "Lloyd", "Forgy", "MacQueen"), trace=FALSE) ## S3 method for class 'kmeans' fitted(object, method = c("centers", "classes"), ...)
– sai saran
Nov 16 '18 at 8:30
1
They will all be used. If you want to use only certain columns then limit the columns in the data frame that you pass to the kmeans function
– Cleland
Nov 16 '18 at 9:32
have u checked the cheat sheet ?
– sai saran
Nov 16 '18 at 7:36
have u checked the cheat sheet ?
– sai saran
Nov 16 '18 at 7:36
@sai sara, I did not check any sheet. I just did some research online and no example showed the criteria of the input data.frame.
– Justin
Nov 16 '18 at 7:54
@sai sara, I did not check any sheet. I just did some research online and no example showed the criteria of the input data.frame.
– Justin
Nov 16 '18 at 7:54
?kmeans can u try this one
– sai saran
Nov 16 '18 at 8:29
?kmeans can u try this one
– sai saran
Nov 16 '18 at 8:29
1
1
Description Perform k-means clustering on a data matrix. Usage kmeans(x, centers, iter.max = 10, nstart = 1, algorithm = c("Hartigan-Wong", "Lloyd", "Forgy", "MacQueen"), trace=FALSE) ## S3 method for class 'kmeans' fitted(object, method = c("centers", "classes"), ...)
– sai saran
Nov 16 '18 at 8:30
Description Perform k-means clustering on a data matrix. Usage kmeans(x, centers, iter.max = 10, nstart = 1, algorithm = c("Hartigan-Wong", "Lloyd", "Forgy", "MacQueen"), trace=FALSE) ## S3 method for class 'kmeans' fitted(object, method = c("centers", "classes"), ...)
– sai saran
Nov 16 '18 at 8:30
1
1
They will all be used. If you want to use only certain columns then limit the columns in the data frame that you pass to the kmeans function
– Cleland
Nov 16 '18 at 9:32
They will all be used. If you want to use only certain columns then limit the columns in the data frame that you pass to the kmeans function
– Cleland
Nov 16 '18 at 9:32
add a comment |
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have u checked the cheat sheet ?
– sai saran
Nov 16 '18 at 7:36
@sai sara, I did not check any sheet. I just did some research online and no example showed the criteria of the input data.frame.
– Justin
Nov 16 '18 at 7:54
?kmeans can u try this one
– sai saran
Nov 16 '18 at 8:29
1
Description Perform k-means clustering on a data matrix. Usage kmeans(x, centers, iter.max = 10, nstart = 1, algorithm = c("Hartigan-Wong", "Lloyd", "Forgy", "MacQueen"), trace=FALSE) ## S3 method for class 'kmeans' fitted(object, method = c("centers", "classes"), ...)
– sai saran
Nov 16 '18 at 8:30
1
They will all be used. If you want to use only certain columns then limit the columns in the data frame that you pass to the kmeans function
– Cleland
Nov 16 '18 at 9:32