Deep Categorization assigns one or more categories to a text. The definition and criteria of those categories — that is, the taxonomy used in the classification — is determined by the model used.
There are two types of models you can use: predefined models, which are the ones MeaningCloud provides, and user-defined models, which you can develop using your own criteria in the deep categorization models console.
These are the settings for this recipe:
Some of the predefined models are part of our vertical packs. You need to have access to them to use them in the classification successfully. If you don't have access to them, make sure to request the free trial or to subscribe to them!
The new columns added to the output dataset will be named using the format "Category [N]", where N is the number of category. The following example uses the dataset and the user-defined model described in this tutorial. The number of categories selected is '1'.