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Posted to issues@spark.apache.org by "Joseph K. Bradley (JIRA)" <ji...@apache.org> on 2015/08/10 20:49:47 UTC
[jira] [Comment Edited] (SPARK-9658) ML 1.5 QA: API: Binary
incompatible changes
[ https://issues.apache.org/jira/browse/SPARK-9658?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14659182#comment-14659182 ]
Joseph K. Bradley edited comment on SPARK-9658 at 8/10/15 6:49 PM:
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1 was intentional. I'm OK with creating a new param though.
2. gammaShape could be given a default. topicConcentration is necessary, I'd say.
3. AFAIK this is a Scala compiler bug, not something we can fix easily.
4. That was intentional. We could put it back, though that would create duplicate parameters with sort of confusing semantics.
5. I like having it in a single place to share the implementation. I know it's simple, but it's easy to mess up by swapping the 2 values.
was (Author: josephkb):
1 was intentional. I'm OK with creating a new param though.
2. gammaShape could be given a default. topicConcentration is necessary, I'd say.
3. AFAIK this is a Scala compiler bug, not something we can fix easily.
4. That was intentional. We could put it back, though that would create duplicate parameters with sort of confusing semantics.
5. Sounds good.
> ML 1.5 QA: API: Binary incompatible changes
> -------------------------------------------
>
> Key: SPARK-9658
> URL: https://issues.apache.org/jira/browse/SPARK-9658
> Project: Spark
> Issue Type: Sub-task
> Components: ML, MLlib
> Affects Versions: 1.5.0
> Reporter: Xiangrui Meng
> Assignee: Xiangrui Meng
> Priority: Blocker
>
> Generated a list of binary incompatible changes using MiMa and filter out some false positives:
> 1. LDA.docConcentration
> It will be nice to keep the old APIs unchanged. For example, we can use “asymmetricDocConcentration”. Then “getDocConcentration" would return the first item if the concentration vector is a constant vector.
> 2. LDAModel.gammaShape / topicConcentration
> Should be okay if we assume that no one extends LDAModel.
> 3. Params.setDefault
> If we have time to investigate this issue. We should put it back.
> 4. LogisticRegressionModel.threshold is missing.
> 5. LogisticRegression.setThreshold shouldn't be in the Params trait. We need to override it anyway.
> Will create sub-tasks for each item.
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