What are the key parameters in an sklearn pipeline?
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What are the key parameters in an sklearn pipeline?
In an sklearn pipeline, key parameters include 'steps', 'memory', and 'verbose'. Would you like to know more about each?
Yes, please explain the 'steps' parameter.
The 'steps' parameter is a list of tuples, where each tuple contains a name and a transformer or estimator. It defines the sequence of transformations and the final estimator.
What does the 'memory' parameter do?
The 'memory' parameter allows you to cache the fitted transformers to avoid recomputing them during cross-validation, which can save time.
Can you give an example of how to set up a pipeline?
Sure! Here's a simple example: Pipeline(steps=[('scaler', StandardScaler()), ('classifier', LogisticRegression())]).
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