Data Frame Error in Unsupervised Random Forest

Dear All,

I've been working on an unsupervised random forest procedure, which seems to work when loading a stored data set (such as Iris); yet but when loading my own dataset which I call EQ3, the same procedure does not work.

Instead, I get the error feedback that:

x must be data.frame or matrix object

However, I have checked the 'class(EQ3)', and my data appears as a 'data.frame'.

And when I use the identical commands to the one suggested by the procedure, namely:

clust.iris <- rf.unsupervised(iris[,1:4], n=n, proximity = TRUE,   silhouettes = TRUE)

Therefore:

clust.EQ3 <-rf.unsupervised(EQ3[,1:9], n =9, proximity = TRUE,  silhouettes = TRUE)

I still get the error message. Any feedback on how to fix this would be appreciated.

Thanks

Hi!

To help us help you, could you please prepare a reproducible example (reprex) illustrating your issue? Please have a look at this guide, to see how to create one:


Short Version

You can share your data in a forum friendly way by passing the data to share to the dput() function.
If your data is too large you can use standard methods to reduce it before sending to dput().
When you come to share the dput() text that represents your data, please be sure to format your post with triple backticks on the line before your code begins to format it appropriately.

```
( example_df <- structure(list(Sepal.Length = c(5.1, 4.9, 4.7, 4.6, 5, 5.4, 4.6, 
5, 4.4, 4.9), Sepal.Width = c(3.5, 3, 3.2, 3.1, 3.6, 3.9, 3.4, 
3.4, 2.9, 3.1), Petal.Length = c(1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 
1.4, 1.5, 1.4, 1.5), Petal.Width = c(0.2, 0.2, 0.2, 0.2, 0.2, 
0.4, 0.3, 0.2, 0.2, 0.1), Species = structure(c(1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L), .Label = c("setosa", "versicolor", "virginica"
), class = "factor")), row.names = c(NA, -10L), class = c("tbl_df", 
"tbl", "data.frame")))
```

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