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Access intermediate feature subset select #1043
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Thanks for the suggestions! Actually, the good news is that this is already possible via Example 11 here: https://rasbt.github.io/mlxtend/user_guide/feature_selection/SequentialFeatureSelector/#example-11-interrupting-long-runs-for-intermediate-results But please feel free to reopen this in case it doesn't work or doesn't fully solve the problem. |
Very sorry to reopen this issue again, I understand from the example you mentioned, Intermidiate Results are accessible upon process Interruption. What I hope do to is retrieve those attributes (no of features selected, & metric score) saved to a variable (or write to a file) after adding every feature in an SFFS, without interrupting. For example, I started running the selection process below on 2 June 2023.
For 2 weeks now, and still way to go, maybe another 2 weeks. Suppose those attributes as accessible, and say saved to a file, I can do some anoalysis of the results after Isn't there any way to write those to a file? |
@rasbt |
For future reference, linking the discussion here: #1051 |
Owning to the fact that Sequential Feature Selection is really a time-consuming preprocessing task.
Wouldn't it be nice to have some way to access immediate features selected while the algorithm keeps running. So for example using
SFFS
with say 100 features to select the best, would be nice at round N, to somehow retrieve feature subset selected at end of the selection round.The text was updated successfully, but these errors were encountered: