[SPARK-6258] Python MLlib API missing items: Clustering

• Type: Sub-task
• Status: Resolved
• Priority: Major
• Resolution: Fixed
• Affects Version/s: 1.3.0
• Fix Version/s: 1.4.0
• Component/s: MLlib, PySpark
• Target Version/s: 1.4.0
• Assignee: Yanbo Liang
• Reporter: Joseph K. Bradley
• Created: 11/Mar/15 01:42
• Updated: 15/May/15 13:53
• Resolved: 15/May/15 10:19

Description

This JIRA lists items missing in the Python API for this sub-package of MLlib.
This list may be incomplete, so please check again when sending a PR to add these features to the Python API.

Also, please check for major disparities between documentation; some parts of the Python API are less well-documented than their Scala counterparts. Some items may be listed in the umbrella JIRA linked to this task.

KMeans

• setEpsilon
• setInitializationSteps

KMeansModel

• computeCost
• k

GaussianMixture

• setInitialModel

GaussianMixtureModel

• k

Completely missing items which should be fixed in separate JIRAs (which have been created and linked to the umbrella JIRA)

• LDA
• PowerIterationClustering
• StreamingKMeans

Issue Links

• Is contained by: SPARK-7536 Audit MLlib Python API for 1.4
• requires: SPARK-6612 Python KMeans parity
• links to: [Github] Pull Request #6087 (yanboliang)