A couple of less obvious facets of getting over the (significant!) hurdle to have an algorithm accepted into mllib (/spark.ml):
- the review time can be *very *long - a few to many months is a typical case even for relatively fast tracked algorithms - you will likely be asked to provide evidence of a strong perceived need within the community/industry for the algorithm These considerations may make it challenging for you to find a yet-unimplemented algorithm that can be completed within a constrained timeframe. 2017-10-20 19:43 GMT-07:00 Manolis Gemeliaris <gemeliarismano...@gmail.com>: > Hello everyone, > > I am an undergraduate student and now looking to do my final year project. > Professor > Minos Garofalakis <http://www.softnet.tuc.gr/~minos/> suggested to me > that as a project , I could find a machine learning algorithm not > implemented by anyone ,in Spark.ml and implement it. > As the topic is related to contributing code (an algorithm implementation) > to Spark, I address to you also. > My question to you is , are there any suggestions about what algorithm is > missing from spark.ml currently that would be a good option to implement? > (e.g. k-means and lda are already there and so is lsvm) > > Thanks in advance. >
