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Currently, within the incubator-mxnet repo there are over 800+ open issues and new ones being generated every day. We would like to be able to ease this process and better handle developers' issues. With the use of labelling, MXNet contributors can filter issues which developers have and so that they can offer their help with the issues users face. As well, this can be useful to bring in new contributors. For example, a Scala expert may know how to handle an issue posted on the MXNet repo regarding the Scala API. They would be able to assess the issue we face on our repo and can easily become a contributor. Today, we employ the label bot today to help ease the issue/pull request labelling process.Given  Given the data which the repository provides of previously labelled issues and pull requests which have been previously labelled, an interesting use case of this data opens up. Based upon the this data of this repository, we are able to provide insights and predictions of labels can provide label predictions on new issues and pull requests. This mechanism will  Overall we can provide a better experience for those who have raised an issue to get a faster response, and it allows for existing and new contributors to better filter for their areas of expertise who are wanting to help out welcoming new developers.

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to the community as we will able to address issues in a more efficient matter. 

Proposal:

The label bot will provide a prediction service to label certain issues and pull requests. We will gather these metrics and accuracy figures, and given a threshold we can have the label bot 

This prediction service offered by the label bot can be useful to the community for labelling certain issues and pull requests based upon certain metrics and accuracy figures. The bot will then be able to provide labels or label recommendations on newly opened issues and pull requests.

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