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https://issues.apache.org/jira/browse/SPARK-14380?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15314617#comment-15314617
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Xinh Huynh edited comment on SPARK-14380 at 6/3/16 10:13 PM:
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Existing algorithms
* KMeans
** Param: initial model, bypassing the random initialization or k-means||
(SPARK-10780)
** PMML (SPARK-11237)
* Gaussian Mixture Model (GMM)
** Param: initial model (will create JIRA, related to warm-start support,
SPARK-11136)
* LDA
** In DistributedLDAModel: topDocumentsPerTopic, topTopicsPerDocument,
topicAssignments (needed for parity?)
** In LocalLDAModel: topicDistribution (for just one document, like
SPARK-10809, needed for parity?), topics (is this the same as topicsMatrix?)
was (Author: xinhh):
Existing algorithms
* KMeans
** Param: initial model, bypassing the random initialization or k-means||
(SPARK-10780)
** PMML (SPARK-11237)
* Gaussian Mixture Model (GMM)
** Param: initial model (will create JIRA, related to warm-start support,
SPARK-11136)
> Review spark.ml parity for clustering
> -------------------------------------
>
> Key: SPARK-14380
> URL: https://issues.apache.org/jira/browse/SPARK-14380
> Project: Spark
> Issue Type: Sub-task
> Components: ML
> Reporter: Joseph K. Bradley
>
> Review parity of spark.ml vs. spark.mllib to ensure spark.ml contains all
> functionality. List all missing items.
> This only covers Scala since we can compare Scala vs. Python in spark.ml
> itself.
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