Hey, Igniters! I prepared some PR for Serializable support in our Vectors. Could you review this: https://github.com/apache/ignite/pull/6378 ?
чт, 28 мар. 2019 г. в 11:47, Алексей Платонов <aplaton...@gmail.com>: > Yep, I definitely agree with you. > > Moreover, such improvement should reduce parallel hierarchies in trainers > and preprocessors, from this point of view preprocessor will be equal to a > trainer. In my opinion, this improvement is very important for ml module > because it can give a flexible hierarchy of components. > > I created a ticket for serializable object support in Vectors: > https://issues.apache.org/jira/browse/IGNITE-11647 > Another related ticket to this thread: > https://issues.apache.org/jira/browse/IGNITE-11642 > > чт, 28 мар. 2019 г. в 11:27, Alexey Zinoviev <zaleslaw....@gmail.com>: > >> Hi, Igniters >> >> The new functionality of building Vectors was merged to Apache Ignite in >> the >> next commit >> < >> https://github.com/apache/ignite/commit/a0a15d62a250defb0db9ec72153ee287830f6a15> >> >> >> This new functionality brings to Ignite ML the new approach of building >> vectors. But in my opinion the shouldn't constrain ourselves with narrow >> understanding of Vector nature as an analogue of double[] array. >> >> I suggest to extend the Vector and Vectorizer API to support Strings and >> another types (like Blobs, Images and etc) as a vector elements. >> >> It brings next advantages: >> * gives a chance to inify the hierarchy of Preprocessing Trainers and >> Model >> Trainers >> * give us a chance to implement ML algorithms working not only with >> doubles >> * unifies our Vectorizers as a first step in our Pipelines >> * drops a lot of unused generics >> * makes one simple requirement to final users: convert their data to >> Vectors >> >> Join to discussion, ML-interested persons and share your opinon here! >> >> >> >> -- >> Sent from: http://apache-ignite-developers.2346864.n4.nabble.com/ >> >
