# textcat vs textcat\_multilabel **URL:** https://support.prodi.gy/t/textcat-vs-textcat-multilabel/4729 **Category:** Uncategorized **Tags:** usage, training, textcat **Created:** [September 27, 2021, 9:17pm UTC](https://support.prodi.gy/t/textcat-vs-textcat-multilabel/4729 "2021-09-27T21:17:18Z") **Posts on this page:** 1 **Showing post:** 3
### Author: ![ines](https://sea2.discourse-cdn.com/flex020/user_avatar/support.prodi.gy/ines/32/3_2.png) [@ines](https://support.prodi.gy/u/ines) #### Post date: [September 28, 2021, 8:10am UTC](https://support.prodi.gy/t/textcat-vs-textcat-multilabel/4729/3 "2021-09-28T08:10:48Z")
> [@VeronicaCPerez](#): > > In theory this is just two mutually exclusive classes, one where I "accept" and another one when I "reject". Why do I get this error? The problem with this is that in practice, you still only have one label (`Sectoral`) that either applies or doesn't. And there might be use cases where you want to combine this dataset with other binary datasets for other labels and train an exclusive or non-exclusive classifier on all the data. The alternative would be for Prodigy to add a label `NOT_SECTORAL` (or `OTHER`), but that feels like a very invasive default behaviour because it really modifies the data. So if you only have one label you're predicting, the easier solution would be to use the `textcat_multilabel` component instead. --- _[View the full topic](https://support.prodi.gy/t/textcat-vs-textcat-multilabel/4729)._