How to use gamultiobj for binary decision variables for features selection?

Question

Nainsi Gupta 2025-6-19

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2177901-how-to-use-gamultiobj-for-binary-decision-variables-for-features-selection

回答： Deepak 2025-6-23

I want to use nsga2 for feature selection, where 1 represent feature is selcted while 0 represent that feature is not selected.

How can i use gamultiobj function for this?

7 个评论
显示 5更早的评论隐藏 5更早的评论

Sam Chak 2025-6-20

在 MATLAB Online 中打开

Hi @Nainsi Gupta

Are you asking whether gamultiobj() functions similarly to the NSGA-II algorithm, which is widely used for solving multi-objective optimization problems? Or, are you seeking alternatives for solving multi-objective optimization problems that specifically involve binary decision variables for feature selection?

If the latter is the case, it is possible to develop an intellectual approach that can be implemented using some of the built-in functions in MATLAB. In feature selection, where "1" indicates that a feature is selected and "0" indicates that a feature is unselected, the selection process must be aligned with the screening criteria.

For example, in a pool of 100 applicants, you may wish to select candidates aged 25 to 35. However, this is only one criterion. Additional criteria could include the number of years of experience in a specific field and the skill level (entry, mid, or senior) associated with the roles being considered.

X   = randi([20, 50], [10, 10])
X = 10×10
  50    46    40    20    40    45    25    23    46
  25    32    24    38    36    33    23    26    29
  32    45    49    34    42    21    28    38    35
  34    35    49    37    26    38    35    20    26
  45    33    27    33    34    36    26    26    33
  24    49    37    39    20    33    37    30    41
  23    38    42    39    41    46    30    38    31
  46    48    21    43    26    22    49    31    36
  31    25    31    29    31    43    39    21    42
  47    37    38    43    49    31    41    45    20
<mw-icon class=""></mw-icon>
<mw-icon class=""></mw-icon>

Sam Chak 2025-6-20

@Nainsi Gupta, In that case, if you provide a small sample of data and describe how you would like a certain feature to be selected, experts in the fields of optimization and operations research can likely recommend appropriate built-in functions to address this problem.

Torsten 2025-6-20

编辑：Torsten 2025-6-20

@Nainsi Gupta

Here are the MATLAB tools for multiobjective optimization. You will have to check by the mathematical description of the problems that can be solved whether the respective solver is suitable for your purpose or not.

https://uk.mathworks.com/discovery/multiobjective-optimization.html

Maybe we can help if you include the mathematical formulation of your optimization problem.

请先登录，再进行评论。

请先登录，再回答此问题。

Answer 1

Deepak 2025-6-23

1
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/2177901-how-to-use-gamultiobj-for-binary-decision-variables-for-features-selection#answer_1566980

Hi @Nainsi Gupta,

I understand that you are looking to use NSGA-II via "gamultiobj" function in MATLAB for binary feature selection, where each feature is represented by a 1 (selected) or 0 (not selected). To do this, you can set the option "PopulationType","bitstring" in optimoptions, which tells the solver to treat each individual as a binary vector. In your objective function, use this binary vector as a mask on your dataset to train a classifier (e.g., SVM), and return two objectives — typically classification error and number of selected features.

This approach allows "gamultiobj" to evolve a Pareto front of solutions that balance feature reduction and predictive performance. You can visualize the trade-off using "gaplotpareto", and select the best solution based on your preference. This method is recommended for binary feature selection tasks.

Please find attached the relevant documentations for reference:

Multiobjective Optimization: www.mathworks.com/discovery/multiobjective-optimization.html

gamultiobj: www.mathworks.com/help/gads/gamultiobj.html

I hope this helps.

0 个评论
显示 -2更早的评论隐藏 -2更早的评论

请先登录，再进行评论。

How to use gamultiobj for binary decision variables for features selection?

7 个评论
显示 5更早的评论隐藏 5更早的评论

回答（1 个）

0 个评论
显示 -2更早的评论隐藏 -2更早的评论

另请参阅

类别

标签

产品

Community Treasure Hunt

How to use gamultiobj for binary decision variables for features selection?

7 个评论 显示 5更早的评论隐藏 5更早的评论

回答（1 个）

0 个评论 显示 -2更早的评论隐藏 -2更早的评论

另请参阅

类别

标签

产品

Community Treasure Hunt

7 个评论
显示 5更早的评论隐藏 5更早的评论

0 个评论
显示 -2更早的评论隐藏 -2更早的评论