What are some effective feature selection techniques in machine learning?

What are some effective feature selection techniques in machine learning?

There are several techniques for feature selection, including filter methods, wrapper methods, and embedded methods. Would you like to know more about a specific type?

Can you explain filter methods?

Filter methods evaluate the relevance of features by their relationship with the target variable, often using statistical tests.

What about wrapper methods?

Wrapper methods evaluate subsets of features by training a model on them and assessing performance, which can be computationally expensive.

Are there any embedded methods?

Yes, embedded methods perform feature selection as part of the model training process, like Lasso regression, which penalizes less important features.