Using FLAML to Optimize Parameters in a scikit-learn Pipeline #1444
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Hello, I'm trying to find examples where you can define a scikit-learn pipeline and use FLAML to automatically search for the optimal parameters of both the preprocessing steps and the estimator (for example TFIDF / Logistic Regression). So far, I haven't come across any. Is this even possible with FLAML? Thanks! |
Answered by
thinkall
Jul 31, 2025
Replies: 1 comment
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Hi Taha (@HessTaha), you can create a customized learner and optimize it with FLAML. Checkout the doc here. Thanks. |
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thinkall
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Hi Taha (@HessTaha), you can create a customized learner and optimize it with FLAML. Checkout the doc here. Thanks.