Hi, There are no examples currently. For unsupervised learning, I think the pattern is straightforward. It would follow the pattern from supervised learning, but without the label input column and with a model having a different transform() behavior.
Reinforcement learning might take a bit more design since I haven't seen work on it so far. I'd recommend making a Discussion JIRA to post a set of requirements and get feedback on a design. Reinforcement learning would be great to have in MLlib. Joseph On Mon, Mar 9, 2015 at 5:21 AM, Egor Pahomov <pahomov.e...@gmail.com> wrote: > Hi, I'm redoing my PR <https://github.com/apache/spark/pull/2731> about > genetic algorithm in new org.apache.spark.ml architecture. Do we have > already some code about handling unsupervised or reinforcement algorithm in > new architecture? If no do we have some tickets on this matter? If no do we > have understanding when it would be doing, and how? > > -- > > > > *Sincerely yoursEgor PakhomovScala Developer, Yandex* >
