contextual-bandit | Contextual Bandit is a PIO Kappa Template | Machine Learning library

by actionml Scala Version: Current License: No License

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kandi X-RAY | contextual-bandit Summary

contextual-bandit is a Scala library typically used in Artificial Intelligence, Machine Learning applications. contextual-bandit has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

The Contextual Bandit is a PIO Kappa Template and so is an online learner. It keeps model up-to-date in real time. As such is gets data from the PIO Kappa Server. From events a model is updated and a predictions are served. Every time there is an input events the model is updated and fresh predictions begin with the next query.

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Support

contextual-bandit has a low active ecosystem.

It has 15 star(s) with 4 fork(s). There are 4 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of contextual-bandit is current.

Quality

contextual-bandit has no bugs reported.

Security

contextual-bandit has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

contextual-bandit does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

contextual-bandit releases are not available. You will need to build from source code and install.

Installation instructions are not available. Examples and code snippets are available.

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contextual-bandit Key Features

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contextual-bandit Examples and Code Snippets

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Community Discussions

Trending Discussions on contextual-bandit

Contextual-Bandit Approach: Algorithm 1 LinUCB with disjoint linear models

QUESTION

Contextual-Bandit Approach: Algorithm 1 LinUCB with disjoint linear models

Asked 2019-Feb-25 at 01:34

I am trying to implement the algorithm called LinUCB with disjoint linear models from this paper "A Contextual-Bandit Approach to Personalized News Article Recommendation" http://rob.schapire.net/papers/www10.pdf

This is the algorithm: Algorithm 1 LinUCB with disjoint linear models

I am confused about the features vector Xt,a (I highlighted on the algorithm). Is the feature vector related to information (context) of the article(arm) or the user?

I would appreciate your help. Thank you

...

ANSWER

Answered 2018-Jul-13 at 22:53

The feature vector x_t,a applies to both the user and the arm.

The vector xt,a summarizes information of both the user ut and arm a, and will be referred to as the context.

Source https://stackoverflow.com/questions/51333710

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install contextual-bandit

You can download it from GitHub.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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