Assisted Modelling should support/read all field types and not error

[Joe_Lipski]

I'm really liking the new assisted modelling capabilities released in 2020.2, but it should not error if the data contains: spatial, blob, date, datetime, or datetime types.

This is essentially telling the user to add an extra step of adding a select before the assisted modelling tool and then a join after the models. I think the tool should be able to read in and through these field types (especially dates) and just not use them in any of the modelling.

An even better enhancement would be to transform date as part of the assisted modelling into something usable for the modelling (season, month, day of week, etc.)

[KylieF]

Hi Joe! Thank you you for submitting your feedback on our Assisted Modeling tools! We appreciate all the feedback we can get on these new tools. Your idea looks good to go to product once the criteria is met, and while I'm sure you've heard me say this a load of times, to anyone passing by and interested in this idea please be sure to check out our Submission Guidelines on how you can support it as well as how this boards work.

[CristonS]

Our machine learning efforts are now focused on the new cloud-based Alteryx Machine Learning solution. AYX Machine Learning supports many data types, including: Natural Language, Text, Postal Code, Categorical, Integer, Double, Boolean, URL, Email, and DateTime. Should the user pass an unsupported data type, AYX ML converts the data to a format that is supported when possible. We encourage users seeking advanced ML capabilities to try AYX ML.