Body: <p>I want to solve a symbolic regression problem with genetic programming. My dataset is similar to <a href="https://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_boston.html" rel="nofollow noreferrer">this one</a>, but I have 30 features, and I want to use only the most sensitive features. I found <a href="https://gplearn.readthedocs.io/en/stable/reference.html#symbolic-regressor" rel="nofollow noreferrer">this library</a> interesting for Symbolic Regression, but could not find the right approach for feature selection.</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-03-07T11:20:27.480Z
Comments.Text: Have you tried to look at the existing feature selection techniques typically used in machine learning? If yes, why aren't they good for you? If not, it may be a good idea to have a look at them. Once you know the answer to your question, feel free to write it below (if it's good ehough) ;)
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-03-10T15:50:03.270Z
Comments.Text: You should probably read this: [Feature Selection to Improve Generalization of
  Genetic Programming for High-Dimensional Symbolic Regression](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7879832).
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-03-10T16:46:56.330Z
Comments.Text: I do not have full access to that paper, but it claims as follows, In this paper, we propose a new feature selection method based on permutation to select features for high-dimensional SR using GP. So, `permutation using GP`. what's it really?
Comments.UserDisplayName: Roman
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-03-10T16:47:57.880Z
Comments.Text: You can find a freely available version of this paper (or a draft) on the web.
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-03-10T17:00:49.633Z
Comments.Text: Is there a python library for GP?
Comments.UserDisplayName: Roman
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-03-10T17:11:55.513Z
Comments.Text: Yes, you can use DEAP. Anyway, if you find an answer to your own question, feel free to write it below, with some details and maybe a link to the references that you used.
Comments.UserDisplayName: nbro
Tags: <genetic-algorithms><feature-selection><genetic-programming><algorithm-request>
Title: How can I select features for a symbolic regression problem to be solved with genetic programming?
UserDisplayName: Roman
ThreadText: # How can I select features for a symbolic regression problem to be solved with genetic programming?
  
  (Asked by: username_0 on 2021-03-05)
  
  I want to solve a symbolic regression problem with genetic programming. My dataset is similar to [this one](https://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_boston.html), but I have 30 features, and I want to use only the most sensitive features. I found [this library](https://gplearn.readthedocs.io/en/stable/reference.html#symbolic-regressor) interesting for Symbolic Regression, but could not find the right approach for feature selection.
  
  **Tags:** genetic-algorithms, feature-selection, genetic-programming, algorithm-request
  > **Comments:**
  > **username_1**: Have you tried to look at the existing feature selection techniques typically used in machine learning? If yes, why aren't they good for you? If not, it may be a good idea to have a look at them. Once you know the answer to your question, feel free to write it below (if it's good ehough) ;)  
  > **username_1**: You should probably read this: [Feature Selection to Improve Generalization of Genetic Programming for High-Dimensional Symbolic Regression](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7879832).  
  > **username_0**: I do not have full access to that paper, but it claims as follows, In this paper, we propose a new feature selection method based on permutation to select features for high-dimensional SR using GP. So, `permutation using GP`. what's it really?  
  > **username_1**: You can find a freely available version of this paper (or a draft) on the web.  
  > **username_0**: Is there a python library for GP?  
  > **username_1**: Yes, you can use DEAP. Anyway, if you find an answer to your own question, feel free to write it below, with some details and maybe a link to the references that you used.  
  
  ---
  
  ## 0 answers
  
  