I would like to use dimensionality reduction algorithm in my pipeline. I have 2k features and I'm using xgboost. My model is rebuilding each day (there are new records that should be involve to training set).
I'm looking for method for dimensionality reduction with out setting
I know that in PCA it shouldn't be set. But I'm looking for method that find something like clusters on my data and then I will use it to train my model. Of course the same flow I'll be using for prediction.
Do you have idea how should I do my data processing for this case?