[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user jkbradley commented on the issue: https://github.com/apache/spark/pull/15770 OK sorry to push @wangmiao1981 ! I just want to make sure this gets in before I no longer have bandwidth for it. If you have the time, would you mind checking the updates I made in the new PR? Thanks! --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user wangmiao1981 commented on the issue: https://github.com/apache/spark/pull/15770 @jkbradley I close this one now. Thanks! --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user wangmiao1981 commented on the issue: https://github.com/apache/spark/pull/15770 @jkbradley Sorry for missing your comments. Anyway, I will close it now. I will choose another one to work on. Thanks! --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user jkbradley commented on the issue: https://github.com/apache/spark/pull/15770 I don't mind; I'll take it. But I'll mark @wangmiao1981 as the main contributor for the PR. Would you mind closing this issue @wangmiao1981 and I'll reopen a new PR under the same JIRA? --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user WeichenXu123 commented on the issue: https://github.com/apache/spark/pull/15770 @wangmiao1981 If you're busy I can help take over this. -:) --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user jkbradley commented on the issue: https://github.com/apache/spark/pull/15770 @wangmiao1981 Do let me know if you're too busy now to resume this; I know it's been a long time. Thanks! --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user jkbradley commented on the issue: https://github.com/apache/spark/pull/15770 Just pinged @yanboliang on JIRA about me taking over shepherding this. It will need at least one update: change Since versions from 2.3.0 to 2.4.0. Sorry for the long wait @wangmiao1981 : ( --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user wangmiao1981 commented on the issue: https://github.com/apache/spark/pull/15770 ping @yanboliang --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user wangmiao1981 commented on the issue: https://github.com/apache/spark/pull/15770 ping @yanboliang --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user WeichenXu123 commented on the issue: https://github.com/apache/spark/pull/15770 LGTM. ping @yanboliang --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user wangmiao1981 commented on the issue: https://github.com/apache/spark/pull/15770 @weichenXu123 Any other comments? Thanks! --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user wangmiao1981 commented on the issue: https://github.com/apache/spark/pull/15770 @WeichenXu123 Thanks for your review and reply! I agree with you that the helper can be discussed later for potential enhancement. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user WeichenXu123 commented on the issue: https://github.com/apache/spark/pull/15770 @wangmiao1981 oh, not a big deal, what I thought is that, user is possible to use `graphx` package to get the `Graph[Double, Double]`, and in `ml` package it cannot accept this format, require user to convert it into dataframe (because `mllib` API is deprecate maybe user do not want to use it). But, this can be discussed in separated JIRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user wangmiao1981 commented on the issue: https://github.com/apache/spark/pull/15770 @WeichenXu123 , for the graph helper, the Mllib has a version takes `Graph[Double, Double]` as a parameter for training. In ML, do we have to provide `DataSet` of `Graph`? Can you specify the requirement? I have addressed your other comments. Thanks! --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user wangmiao1981 commented on the issue: https://github.com/apache/spark/pull/15770 I will address the review comments soon. Thanks! @WeichenXu123 --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user WeichenXu123 commented on the issue: https://github.com/apache/spark/pull/15770 @wangmiao1981 Sorry for delay, I will take a look later, thanks! --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
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Github user wangmiao1981 commented on the issue: https://github.com/apache/spark/pull/15770 @WeichenXu123 I have made changes based on your comments. Thanks! --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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Github user wangmiao1981 commented on the issue: https://github.com/apache/spark/pull/15770 info] Main Scala API documentation successful. [error] (spark/javaunidoc:doc) javadoc returned nonzero exit code [error] Total time: 95 s, completed Aug 15, 2017 4:59:59 PM [error] running /home/jenkins/workspace/SparkPullRequestBuilder/build/sbt -Phadoop-2.6 -Pmesos -Pkinesis-asl -Pyarn -Phive-thriftserver -Phive unidoc ; received return code 1 It seems irrelevant. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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Github user wangmiao1981 commented on the issue: https://github.com/apache/spark/pull/15770 @WeichenXu123 Thanks for reviewing! I will address the comments soon. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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Github user wangmiao1981 commented on the issue: https://github.com/apache/spark/pull/15770 @yanboliang Can you take a look first? Thanks! --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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Github user wangmiao1981 commented on the issue: https://github.com/apache/spark/pull/15770 @jkbradley can you take a look? Thanks! --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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Github user wangmiao1981 commented on the issue: https://github.com/apache/spark/pull/15770 It passed at local. I will fix the issue. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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Github user wangmiao1981 commented on the issue: https://github.com/apache/spark/pull/15770 @jkbradley I changed the input data format by using (list of neighbor IDs, list of weights), which are two columns of the input dataset. For the result, I appended the predicted cluster ids to the input dataset by joining the assignment dataset by col `id`. This is an initial implementation. Please take a look. Thanks! --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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Github user wangmiao1981 commented on the issue: https://github.com/apache/spark/pull/15770 Update: Sorry for the delay. I am working on some other items. Now, I am using (node-id, list of neighbor IDs, list of weights) by adding two additional columns. I will push soon. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user wangmiao1981 commented on the issue: https://github.com/apache/spark/pull/15770 Option 2 doesn't break our pipeline scheme which only appends the result column to the input dataframe. Besides the discussions above, the graph is undirected and the weight list will appear twice for two nodes, while Option 1 only stores the weights once. Let me try Option 2 today. Thanks! --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user thunterdb commented on the issue: https://github.com/apache/spark/pull/15770 Note that any of these formats would cause trouble for a graph with high centrality (lady gaga in the twitter graph). That being said, I do not have a strong opinion as to which option we pick, in order to move things along. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user jkbradley commented on the issue: https://github.com/apache/spark/pull/15770 Yep, that's correct. Everyone, please let me know if you disagree. Also, if we do go with Option 2 above, then the input schema could be a few possible things: * list of (neighbor ID, weight) * pro: ensures # neighbors = # weights * con: nesting can be annoying to work with * (list of neighbor IDs, list of weights) * pro: Easier to support unweighted graphs by omitting list of weights. Avoid nesting. * con: could have invalid input with mismatched numbers of neighbors, weights * Vector (of length # neighbors) * pro: Familiar data type. Ensures # neighbors = # weights. * con: If we later support passing raw features which are used to compute a similarity matrix within PIC, then this could confuse users. I'm ambivalent about these schema options. What do you think? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user wangmiao1981 commented on the issue: https://github.com/apache/spark/pull/15770 @jkbradley Thanks for your reply! I quickly go through your suggestions. If I understand correctly, you prefer making it a `Transformer`, as we previously discussed, but changing the input data to fit into to the pipeline. Right? Let me think about details and evaluate each options before making the changes. Thanks! --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user jkbradley commented on the issue: https://github.com/apache/spark/pull/15770 Sorry for my absence from recent conversation! I agree there is no clear answer for handling input and output schema. Some options: * Option 1: same as RDD/GraphX-based API * Input: Each Row is 1 edge. DataFrame represents a graph. * Output: [node ID, cluster ID] * Option 2: take adjacency list * Input: Each Row has [node ID, list of neighbor IDs, list of neighbor edge weights]. DataFrame represents a graph. * Output: Append column for "cluster ID" * Option 3: take feature vectors --> This is another use of PIC from the original paper. Given feature vectors, compute a similarity matrix using some distance, and then run PIC as we do now. We won't do this now, but we could add it as an option in the future. * Input: Each Row has [node ID, feature vector]. DataFrame does *not* represent a graph. * Output: Append columns for "cluster ID" and "adjacency list" It sounds like Option 1 is the main one being considered right now. What do you think of Option 2 though to keep it as a row->row Transformer? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user wangmiao1981 commented on the issue: https://github.com/apache/spark/pull/15770 @thunterdb @yanboliang Do we reach an agreement on whether to make it a transformer or an estimator now? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user yanboliang commented on the issue: https://github.com/apache/spark/pull/15770 @thunterdb I have two concerns about making PIC as an Estimator: * As your suggestion, model's transform will introduce extra data shuffle compared with the original implementation. * It can not fit into the pipeline well, since both the estimator ```fit``` and model ```transform``` method should work on the dataset with same schema, like: ``` val model = new ALS().fit(dataset) model.transform(dataset) ``` But in your suggestion, the input of PIC estimator is the edges or RDD[(Long, Long, Double)], the input of PIC model is the vertices ID. I totally agree making PIC as a Transformer is tricky, but I did not find a better way. Thanks. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user wangmiao1981 commented on the issue: https://github.com/apache/spark/pull/15770 @thunterdb Per discussion with Yanbo, there is one concern of making it an Estimator. For every `transform`, there is an additional data shuffle. cc @yanboliang @jkbradley Thanks! --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user thunterdb commented on the issue: https://github.com/apache/spark/pull/15770 @wangmiao1981 yes I had seen the discussions there. I believe that eventually PIC should be moved into graphframes, but we can have a simple API in `spark.ml` for the time being. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user wangmiao1981 commented on the issue: https://github.com/apache/spark/pull/15770 I am checking ALS out to understand your suggestions. Thanks! --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user wangmiao1981 commented on the issue: https://github.com/apache/spark/pull/15770 Yanbo Liang added a comment - 02/Nov/16 09:30 - edited I'm prefer to #1 and #3, but it looks like we can achieve both goals. Graph can be represented by GraphX/GraphFrame or DataFrame/RDD. PIC model can be trained on both of them, but we use GraphX operators in the internal implementation which means input data should be converted to GraphX representation if it's RDD of tuples. So it's straight forward to make PIC as one of the algorithms in GraphX(or GraphFrame when it is merged back into Spark). However, users may load their graph as DataFrame/RDD and transform via ML Pipeline which should also be supported, so it's better we can wrap PIC of GraphX/GraphFrame as an Pipeline stage and then ML users can use it as well. For some historical reasons(we don't want to add new features to GraphX), I propose to split this task into the following step: Put PIC in Pipeline as a Transformer, use the GraphX operators in the implementation (This is consistent with Joseph K. Bradley's proposal). Add PIC algorithms to GraphFrames when it is merged into Spark. Make the ML PIC as a wrapper to call the GraphFrames PIC implementation. I think this scenario should be better for different users(ML users and GraphFrames users), but still open to hear your thoughts. Thanks. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user wangmiao1981 commented on the issue: https://github.com/apache/spark/pull/15770 Joseph K. Bradley added a comment - 31/Oct/16 18:14 Miao Wang Sorry for the slow response here. I do want us to add PIC to spark.ml, but we should discuss the design before the PR. Could you please close the PR for now but save the branch to re-open after discussion? Let's have a design discussion first. I agree that the big issue is that there isn't a clear way to make predictions on new data points. In fact, I've never heard of people trying to do so. Has anyone else? Assuming that prediction is not meaningful for PIC, then I don't think the algorithm fits within the Pipeline framework, though it's debatable. I see a few options: Put PIC in Pipelines as a Transformer, not an Estimator. We would just need to document that it is a very expensive Transformer. Put PIC in spark.ml as a static method. We may have to do this anyways to support all of spark.mllib's Statistics. Put PIC in GraphFrames (and push harder for GraphFrames to be merged back into Spark, which will include a much longer set of improvements). My top choice is PIC as a Transformer. What do you think? CC Yanbo Liang Seth Hendrickson Nick Pentreath opinions? sethah Seth Hendrickson added a comment - 31/Oct/16 22:40 This seems like it fits the framework of a feature transformer. We could generate a real-valued feature column using PIC algorithm where the values are just the components of the pseudo-eigenvector. Alternatively we could pipeline a KMeans clustering on the end, but I think it makes more sense to let users do that themselves - but that's up for debate. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user wangmiao1981 commented on the issue: https://github.com/apache/spark/pull/15770 @thunterdb Thanks for your response. In the original JIRA, we have discussed why we want it to be a transformer. Let me find it and post it here. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #15770: [SPARK-15784][ML]:Add Power Iteration Clustering to spar...
Github user thunterdb commented on the issue: https://github.com/apache/spark/pull/15770 You are right, I had forgotten that for this algorithm, the input is the edges, and the output is the label for each of the vertices. This is a tricky algorithm to put as a transformer, since it does not follow the usual convention that data should only be appended to the dataframe. I suggest we follow the same example as ALS the mllib implementation of PIC: - let's make it an estimator that returns a model: the model contains the labels for each of the points in a dataframe (the current output of transform) - the model's transform method now takes points with an id, and joins it with the models to append a column of labels. This is the same as ALS. If we do not follow this pattern, then the model selection algorithms are not going to work. What do you think? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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