Answers.Body: <p>In the current state, Deep learning for Tabular is not very popular, so it is very hard to find libraries that support feature importance. However, <a href="https://github.com/dreamquark-ai/tabnet" rel="nofollow noreferrer">TabNet</a> also provides the <code>model.features_importance_</code> metrics to be used as usual. <a href="https://www.kaggle.com/code/optimo/tabnet-with-loop-feature-engineering-explained#Basic-Features-importance" rel="nofollow noreferrer">This Kaggle notebook</a> provides an example on how to use just that.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2023-01-19T06:55:15.760Z
Answers.LastActivityDate: 2023-01-19T06:55:15.760Z
Answers.UserDisplayName: Minh-Long Luu
Body: <p>For tree methods, I can plot the feature importance plot from <code>tree.feature_importances_</code> in sklearn, is this achievable in deep learning (neural networks)?</p>
  <p>Is there a way to see the feature importance in deep learning (neural networks)?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2023-01-19T10:35:40.650Z
Comments.Text: Are you asking how to compute this conceptually or are you asking for a library does it? If the latter, then this question is off-topic. If the former and the latter, then it's on-topic. If the former, it's on-topic.
Comments.UserDisplayName: nbro
Tags: <neural-networks><deep-learning><decision-trees><feature-selection>
Title: Is there a way to see the feature importance in deep learning (neural networks)?
UserDisplayName: user900476
ThreadText: # Is there a way to see the feature importance in deep learning (neural networks)?
  
  (Asked by: username_0 on 2023-01-18)
  
  For tree methods, I can plot the feature importance plot from `tree.feature_importances_` in sklearn, is this achievable in deep learning (neural networks)?
  
  Is there a way to see the feature importance in deep learning (neural networks)?
  
  **Tags:** neural-networks, deep-learning, decision-trees, feature-selection
  > **Comments:**
  > **username_1**: Are you asking how to compute this conceptually or are you asking for a library does it? If the latter, then this question is off-topic. If the former and the latter, then it's on-topic. If the former, it's on-topic.  
  
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  ## 1 answers
  
  ### Answer by username_2 on 2023-01-19. Score: 1
  
  In the current state, Deep learning for Tabular is not very popular, so it is very hard to find libraries that support feature importance. However, [TabNet](https://github.com/dreamquark-ai/tabnet) also provides the `model.features_importance_` metrics to be used as usual. [This Kaggle notebook](https://www.kaggle.com/code/optimo/tabnet-with-loop-feature-engineering-explained#Basic-Features-importance) provides an example on how to use just that.
  
  
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