Machine Learning Classification

How can I find the best subset of the predictors for a classification problem??
Any kind of help will be appreciated. Thanks in advance.

If I understood correctly, you should look for unsupervised learning, explainable AI and dimensionality reduction techniques. Possible starting points are: MLJ.jl models, ExplainableAI.jl, ShapML.jl and CounterfactualExplanations.jl

No, no. When we are build a model to dataset, it is not the case that all the predictors that are given in the data is important. So, to choose the best subset of the set of predictors, i have learnt four techniques best subset selection, forward selection, backward selection and hybrid selection. So, how we can apply these methods, that was my question. No need to go for unsupervised learning.

Oh ok. That’s feature selection. A quick google search resulted in FeatureSelectors.jl. Scikit-learn has nice options (julia package ScikitLearn.jl may enable access to them)