If I understand correctly, the current approach learns and transforms at the same time. As a consequence you can't learn on a subset (train set), then transform the whole dataset. It would be nice to be able to train a model then apply it to incoming data.
(It's something that is very easy with some algorithms (PCA), but more difficult with others.)
It is not possible for most of the techniques. As far as i know, for the implemented algorithms it is only possible for PCA. I wanted to keep the API as consistent as possible, therefore i didn't added it.
If I understand correctly, the current approach learns and transforms at the same time. As a consequence you can't learn on a subset (train set), then transform the whole dataset. It would be nice to be able to train a model then apply it to incoming data.
(It's something that is very easy with some algorithms (PCA), but more difficult with others.)