Thank you.
________________________________ From: Nikhil Kak <n...@pivotal.io> Sent: Friday, July 20, 2018 4:56 PM To: user@madlib.apache.org Subject: Re: Learning with sparse vector format data Hi Luyao, Thanks for trying out MADlib. Most of the modules including logistic regression do not support sparse vector columns. However kmeans http://madlib.apache.org/docs/latest/group__grp__lda.html does support it. MADlib: Latent Dirichlet Allocation<http://madlib.apache.org/docs/latest/group__grp__lda.html> madlib.apache.org Latent Dirichlet Allocation (LDA) is a generative probabilistic model for natural texts. It is used in problems such as automated topic discovery, collaborative filtering, and document classification. Let us know if you have more questions. Thanks, Nikhil Kak On Thu, Jul 19, 2018 at 11:47 AM LUYAO CHEN <luyao_c...@hotmail.com<mailto:luyao_c...@hotmail.com>> wrote: Hi MADlib User Community, I am new for MADlib. I have a question regarding the data in sparse vector format - Can I run the learning in sparse vector format? For example, logistic regression. Seem the parameters assume that the data was stored in the table. In my scenario, I have 10 thousand if features, so that store them in the sparse vector format would be a better solution. Thanks, Luyao
