I'm trying to run K-means algorithm with predefined centroids. I have had a look at the following posts:

1.[R k-means algorithm custom centers](https://stackoverflow.com/questions/29605911/r-k-means-algorithm-custom-centers)

2.[Set static centers for kmeans in R](https://stackoverflow.com/questions/47997906/set-static-centers-for-kmeans-in-r)

However, every time I run the command:

```
km = kmeans(df_std[,c(10:13)], centers = centroids)

```

I get the following error:

```
**Error: empty cluster: try a better set of initial centers**

```

I have defined the centroids as:

```
centroids = matrix(c(140.12774, 258.62615, 239.36800, 77.43235,
                      33.37736, 58.73077,  68.80000,  12.11765,
                     0.8937264, 0.8118462, 0.8380000, 0.8052941,
                     11.989858, 12.000000, 8.970000,  1.588235),
ncol = 4, byrow = T)

```

And my data, is a subset of a data frame say: df\_std. It has been scaled already

```
df_std[,c(10:13)]

```

I'm wondering why would the system give the above error?
Any help on this would be highly appreciated!