Feature selection is fairly easy in e.g. Python's
scikit-learn which sports a module and tutorials or MATLAB.
Mathematica even touts that it uses feature selection in its automated machine learning algorithms, though I've had trouble finding much more on this, especially anything in Mathematica documentation. Related SE posts are How to know the internal pre-processing of automatic machine learning function
Classify? and How to view ClassifierFunction's preprocessed data?
I could probably use Mathematica's
Correlation functions for some basic feature selection. I'm also aware that I could try different combinations of features and choose ones with higher accuracy, as described in How can I determine the importance of variables from Classify?.
Predict, there's some option I'm overlooking..
I'm also aware of and a moderate user of the Wolfram Client Library for Python, in which case I could use some of
scikit-learn's functionality, though it would be nice to know if Mathematica has built-in options or if someone has developed some sophisticated code to do this.