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https://issues.apache.org/jira/browse/SPARK-7529?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14562199#comment-14562199
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Joseph K. Bradley commented on SPARK-7529:
------------------------------------------
*spark.mllib: Issues found in a pass through the spark.mllib package*
* _This is not yet complete, but I'm saving my work partway. Will update soon._
h3. Classification
LogisticRegressionModel + SVMModel
* scala.Option<Object> getThreshold()
NaiveBayesModel
* "Java-friendly constructor": NaiveBayesModel(Iterable<Object> labels,
Iterable<Object> pi, Iterable<Iterable<Object>> theta)
h3. Clustering
DistributedLDAModel
* RDD<scala.Tuple2<Object,Vector>> topicDistributions()
GaussianMixtureModel + KMeansModel + NaiveBayesModel
* RDD<Object> predict(RDD<Vector> points)
StreamingKMeans
* DStream<Object> predictOn(DStream<Vector> data)
* <K> DStream<scala.Tuple2<K,Object>>
predictOnValues(DStream<scala.Tuple2<K,Vector>> data, scala.reflect.ClassTag<K>
evidence$1)
h3. Evaluation
AreaUnderCurve
* static double of(scala.collection.Iterable<scala.Tuple2<Object,Object>> curve)
* static double of(RDD<scala.Tuple2<Object,Object>> curve)
BinaryClassificationMetrics
* LOTS (everything taking/returning an RDD)
RankingMetrics constructor
* RankingMetrics(RDD<scala.Tuple2<Object,Object>> predictionAndLabels,
scala.reflect.ClassTag<T> evidence$1)
h3. Feature
Word2VecModel
* scala.Tuple2<String,Object>[] findSynonyms
h3. Linalg
SparseMatrix
* static SparseMatrix fromCOO(int numRows, int numCols,
scala.collection.Iterable<scala.Tuple3<Object,Object,Object>> entries)
Vectors
* static Vector sparse(int size,
scala.collection.Seq<scala.Tuple2<Object,Object>> elements)
BlockMatrix
* RDD<scala.Tuple2<scala.Tuple2<Object,Object>,Matrix>> blocks()
** _This issue appears in the constructors too._
> Java compatibility check for MLlib 1.4
> --------------------------------------
>
> Key: SPARK-7529
> URL: https://issues.apache.org/jira/browse/SPARK-7529
> Project: Spark
> Issue Type: Sub-task
> Components: ML, MLlib
> Affects Versions: 1.4.0
> Reporter: Xiangrui Meng
> Assignee: Joseph K. Bradley
>
> Check Java compatibility for MLlib 1.4. We should create separate JIRAs for
> each possible issue.
> Checking compatibility means:
> * comparing with the Scala doc
> * verifying that Java docs are not messed up by Scala type incompatibilities
> (E.g., check for generic "Object" types where Java cannot understand complex
> Scala types. Also check Scala objects (especially with nesting!) carefully.
> * If needed for complex issues, create small Java unit tests which execute
> each method. (The correctness can be checked in Scala.)
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