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[Idea]: implement incremental (online) machine learning algorithms #37

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Description

Idea

The goal of this idea is to implement incremental machine learning algorithms to allow for real-time regression and classification. Such online algorithms would allow for point-by-point data processing and avoid the sometimes costly overhead of batch processing. Online algorithms are particularly useful in data streaming contexts (e.g., user clicks, photon collection, etc).

While stdlib includes some incremental algorithms (binary classification, k-means, and stochastic gradient descent regression), the project would benefit from additional algorithms.

Individuals interested in pursuing this idea should be prepared to research possible algorithms and propose specific APIs.

Expected Outcomes

stdlib will expose one or more additional APIs for incremental machine learning.

Involved Software

No other software is necessary.

Prerequisite Knowledge

JavaScript, Node.js.

Difficulty

Intermediate. In order to implement ML algorithms, individuals will likely need to consult reference implementations written in other languages. Porting from these implementations may not be straightforward depending on the features involved.

Project Length

90/175/350 hours. Can be scoped accordingly.

Potential Mentors

@kgryte @Planeshifter

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    difficulty: 3Likely to be challenging but manageable.ideaPotential GSoC project idea.priority: lowLow priority.tech: javascriptInvolves programming in JavaScript.tech: nodejsRequires developing with Node.js.

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