Current version of stacked_genelarization continue to holt all stage0 model after fitting.
But in case of huge stacking model (~100), stacked_genelarization needs huge memory.
By adding lazy evaluation, I want to improve memory management.
i.e. hold stage0 model only when predicting, and release memory.
(Save model to joblib cache and load only when needed.)
Current version of stacked_genelarization continue to holt all stage0 model after fitting.
But in case of huge stacking model (~100), stacked_genelarization needs huge memory.
By adding lazy evaluation, I want to improve memory management.
i.e. hold stage0 model only when predicting, and release memory.
(Save model to joblib cache and load only when needed.)