The logic of Vector Linear Regression
t_ghanbarpour
Member Posts: 5 Contributor I
Hi,
I have searched about vector linear regression on the web about the mathematical logic of the algorithm but didn't find anything.
It would help a lot if anybody helps me out with the mathematical aspect of vector linear regression and its difference with linear regression.
Thanks.
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MartinLiebig Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University Professor Posts: 3,453 RM Data Scientist

MartinLiebig Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University Professor Posts: 3,453 RM Data Scientist
Answers
Hallo,
Please, have a look at these two videos produced by Ingo, one of the most senior persons from Rapidminer:
https://www.youtube.com/watch?v=maCLzxLyX6U
https://www.youtube.com/watch?v=YsiWisFFruY
With a quick search along "Vector Linear Regression" & "Linear Regression", it is easy to find more formal (mathematical) explanation (algebra, vector theory).
Bonne chance,
Maerkli
"Ingo, one of the most senior persons from Rapidminer"
FYI @IngoRM is one of two founders of RapidMiner (the other is @RalfKlinkenberg) and they literally wrote the first versions of RapidMiner back 10 years ago (it was originally called YALE). So yeah, @IngoRM is definitely one of our more senior members!
Scott
@sgenzer the operative word is "senior!" hehehe!
Thank you for the response.
But as you know support vector machines (and SVR) are something different than vector linear regression.
So, any difference between vector linear regression and support vector regression?
Thank you,
I implemented both linear regression and vector linear regression on a single labeled dataset, but the results were totally different!
So, any other idea about the differences of these two algorithms?
Thank you, it worked!
I unchecked the 'eliminate colinear features' and changed the feature selection to 'Iterative TTest'. Now the linear regression and vector linear regression are giving same results.