How to build a multiple output regression model?
조회 수: 36 (최근 30일)
이전 댓글 표시
The problem I am trying to solve is to build a regression model that maps "n" independent variables to "m" response variables.
I have nearly 35000 data points for each of the "n" independent variables and I want to build a regression model using this 35000 X n space to obtain relations to 35000 corresponding data points to each of the "m" response variables (35000 X m response space). Note: eveyrthing is a "double" data type
I found 'fitrauto" function for hyper parameter optimzation for each of the output variables individually by choosing the best regression model and optimising the corresponsing parameters. But what I would like to know is if there is an equivalent function that can build and optimize a regression model for my multi-input, multi-output case.
Schematically what i would like to do:
table_with_data=table(var1, var2, ..., varn)
regression_model=awesome_function(table_with_data, {response_variables}) %[hopefully a function similar to fitrauto so that i don't manually need to evaluate different regression models]
here {response variables}=set of variables {var_a, var_b,...var_m}
I would like to know if there is such an awesome_function, if not how could I implement one?
댓글 수: 0
답변 (1개)
Vimal Rathod
2021년 6월 15일
Hi,
Currently there might not be any function like 'fitrauto' for multi-response variable regression but you could create your custom function using a bayesian model to optimize hyperparameters using the following link.
댓글 수: 1
Alejandro Plata
2023년 6월 5일
If you don't mind me asking, which MATLAB functions support multi-response regression? I have been searching through mathworks and have been entirely unable to find a suitable function. Thank you!
참고 항목
카테고리
Help Center 및 File Exchange에서 Sequence and Numeric Feature Data Workflows에 대해 자세히 알아보기
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!