Combining Two Different models - One built on text attributes and one built on numeric attributes
Hello,
I am working on a college research project and am looking for solutions to an issue I am facing. I want to build two seperate models, one utilising the text data and one utilising the numeric data. I plan on applying Text Preprocessing steps to the text model and traditional pre processing steps for the numeric model. However, I am unsure of how is the best way of combining the power of both these models into a single model and was hoping someone could kindly shed some light on it for me?
Thanks in advance for any responses.
Kind Regards,
Barry
I am working on a college research project and am looking for solutions to an issue I am facing. I want to build two seperate models, one utilising the text data and one utilising the numeric data. I plan on applying Text Preprocessing steps to the text model and traditional pre processing steps for the numeric model. However, I am unsure of how is the best way of combining the power of both these models into a single model and was hoping someone could kindly shed some light on it for me?
Thanks in advance for any responses.
Kind Regards,
Barry
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Hi Barry,
If you are using "text vectorization" for text preprocessing, you can directly apply it by "Apply Model". Take a look at the tutorial process for text vectorization operator, which has applied both text preprocessing models and predictive models.


Of course, you can group models and apply the grouped model just once. See attached for details.
If you are using the "text processing" extension for text preprocessing, you will not have a "model", but you can re-use the text processing sub-process on any new documents with the wordlist from your training set.. The sub-process for text pre-processing step can be shared as building blocks, or even shipped as a custom operator.
HTH!
Cheers,
YY
If you are using "text vectorization" for text preprocessing, you can directly apply it by "Apply Model". Take a look at the tutorial process for text vectorization operator, which has applied both text preprocessing models and predictive models.


Of course, you can group models and apply the grouped model just once. See attached for details.
If you are using the "text processing" extension for text preprocessing, you will not have a "model", but you can re-use the text processing sub-process on any new documents with the wordlist from your training set.. The sub-process for text pre-processing step can be shared as building blocks, or even shipped as a custom operator.
HTH!
Cheers,
YY
If you are using "text vectorization" for text preprocessing, you can directly apply it by "Apply Model". Take a look at the tutorial process for text vectorization operator, which has applied both text preprocessing models and predictive models.
Of course, you can group models and apply the grouped model just once. See attached for details.
If you are using the "text processing" extension for text preprocessing, you will not have a "model", but you can re-use the text processing sub-process on any new documents with the wordlist from your training set.. The sub-process for text pre-processing step can be shared as building blocks, or even shipped as a custom operator.
HTH!
Cheers,
YY