Hi Grant, Very good release announcement. I propose that we deprecate a lot more, I think we should be aggressive here to pave the way for a clean and slim 1.0 release.
I propose to additionally deprecate the following algorithms, as to my state of knowledge, they are not actively used: Collaborative Filtering: - all recommenders in o.a.m.cf.taste.impl.recommender.knn - the TreeClusteringRecommender in o.a.m.cf.taste.impl.recommender - the SlopeOne implementations in o.a.m..cf.taste.hadoop.slopeone and o.a.m.cf.taste.impl.recommender.slopeone - the distributed pseudo recommender in o.a.m.cf.taste.hadoop.pseudo Classification: - the Hidden Markov Models in o.a.m.classifier.sequencelearning.hmm Clustering - Fuzzy k-Means o.a.m.clustering.fuzzykmeans - Spectral k-Means in o.a.m.clustering.spectral Math - the tooling in o.a.m.math.stats.entropy Furthermore, I think we should deprecate the Lanczos implementation in o.a.m.math.hadoop.decomposer and port all code that uses it to SSVD. To all users and other committers, this is a biased first proposal, please shout, if you see things different and want to have things kept. Best, Sebastian On 08.06.2013 16:42, Grant Ingersoll wrote: > More tests are always welcome. > > On Jun 8, 2013, at 10:29 AM, Ravi Mummulla <ravi.mummu...@gmail.com> wrote: > >> Hi Grant, >> Regarding 1.0 plans, do we also want to include a note on adding tests >> where they don't exist or improving them where needed or is that implicit? >> >> Thanks. >> >> >> On Sat, Jun 8, 2013 at 3:55 AM, Grant Ingersoll <gsing...@apache.org> wrote: >> >>> Hi Mahouts, >>> >>> A full copy of proposed draft release notes are up at >>> https://cwiki.apache.org/confluence/display/MAHOUT/Release+0.8. Please >>> add/edit as appropriate. >>> >>> IN PARTICULAR, PLEASE PAY CLOSE ATTENTION TO THE SECTION LABELLED __FUTURE >>> PLANS__, which I have included below. This is purely my own opinion, but I >>> think it reflects conversations I've had w/ both Robin and Sebastian at >>> Berlin Buzzwords. I'm also interested in opinions on my proposed >>> deprecation plan (which I haven't discussed with anyone) which is put forth >>> in the 1.0 plans below. >>> >>> -------------------------- DRAFT ------------------------- >>> FUTURE PLANS >>> >>> 0.9 >>> >>> As the project moves towards a 1.0 release, the community is working to >>> clean up and/or remove parts of the code base that are under-supported or >>> that underperform as well as to better focus the energy and contributions >>> on key algorithms that are proven to scale in production and have seen >>> wide-spread adoption. To this end, in the next release, the project is >>> planning on removing support for the following algorithms unless there is >>> sustained support and improvement of them before the next release. >>> >>> The algorithms to be removed are: >>> - From Clustering: >>> Dirichlet >>> MeanShift >>> MinHash >>> - From Classification (both are sequential implementations) >>> Winnow >>> Perceptron >>> - Frequent Pattern Mining >>> - Collaborative Filtering >>> GSI: DO ANY GO HERE? >>> - Other >>> GSI: ANYTHING? >>> >>> If you are interested in supporting 1 or more of these algorithms, please >>> make it known on d...@mahout.apache.org and via JIRA issues that fix >>> and/or improve them. Please also provide supporting evidence as to there >>> effectiveness for you in production. >>> >>> 1.0 PLANS >>> >>> Our plans as a community are to focus 0.9 on cleanup of bugs and the >>> removal of the code mentioned above and then to follow with a 1.0 release >>> soon thereafter, at which point the community is committing to the support >>> of the algorithms packaged in the 1.0 for at least two minor versions after >>> their release. In the case of removal, we will deprecate the functionality >>> in the 1.(x+1) minor release and remove it in the 1.(x+2) release. For >>> instance, if feature X is to be removed after the 1.2 release, it will be >>> deprecated in 1.3 and removed in 1.4. >>> >>> ------------------- DRAFT ---------------------- >>> >>> -Grant >> >> >> >> >> -- >> Thanks. > > -------------------------------------------- > Grant Ingersoll | @gsingers > http://www.lucidworks.com > > > > > >
