Question related to the book
Edward Wiskers <[email protected]>
| Newsgroups | gmane.comp.ai.weka |
|---|---|
| Message-ID | <CAPcuOJ0M-2iaP99vse_Ni3dnQQ3v9SfeCn=yODUywoBxyowwXA@mail.gmail.com> |
Hi all, In the last version of the book, especially on page 418, it was highlighted that Representation learning techniques transform features into some intermediate representation prior to mapping them to final predictions. Can any of the authors explain the idea behind *Representation learning* techniques? How it differs from classical machine learning and provide an example algorithm related to this category in Weka? Thanks in advance. Edward _______________________________________________ Wekalist mailing list -- [email protected] Send posts to [email protected] To unsubscribe send an email to [email protected] To subscribe, unsubscribe, etc., visit https://list.waikato.ac.nz/postorius/lists/wekalist.list.waikato.ac.nz List etiquette: http://www.cs.waikato.ac.nz/~ml/weka/mailinglist_etiquette.html