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While a rich set of algorithms is an important goal for MLLib, scaling the project requires that maintainability, consistency, and code quality come first.  New algorithms should

•  Be widely known
• Be used and accepted (academic citations and concrete use cases can help justify this)
• Be highly scalable
• Be well documented
• Have APIs consistent with other algorithms in MLLib that accomplish the same thing
• Come with a reasonable expectation of developer support.

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