Well if it is easy to convert I suppose it only costs memory. Sent from my iPhone
> On Apr 22, 2014, at 11:32, "Dmitriy Lyubimov (JIRA)" <[email protected]> wrote: > > > [ > https://issues.apache.org/jira/browse/MAHOUT-1518?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13977085#comment-13977085 > ] > > Dmitriy Lyubimov commented on MAHOUT-1518: > ------------------------------------------ > > data frames are different in that they can hold data types other than double > as element. as such, I imagine the intersection of their behavior with matrix > is going to be fairly limited (some ordinal slicing operators, perhaps), as > well as they would have different in-core and persistence backing. > > For that reason, i would resist the urge to imply they have too much in > common with DRMs -- even by name. > > >> Preprocessing for collaborative filtering with the Scala DSL >> ------------------------------------------------------------ >> >> Key: MAHOUT-1518 >> URL: https://issues.apache.org/jira/browse/MAHOUT-1518 >> Project: Mahout >> Issue Type: New Feature >> Components: Collaborative Filtering >> Reporter: Sebastian Schelter >> Assignee: Sebastian Schelter >> Fix For: 1.0 >> >> Attachments: MAHOUT-1518.patch >> >> >> The aim here is to provide some easy-to-use machinery to enable the usage of >> the new Cooccurrence Analysis code from MAHOUT-1464 with datasets >> represented as follows in a CSV file with the schema _timestamp, userId, >> itemId, action_, e.g. >> {code} >> timestamp1, userIdString1, itemIdString1, “view" >> timestamp2, userIdString2, itemIdString1, “like" >> {code} > > > > -- > This message was sent by Atlassian JIRA > (v6.2#6252)
