confidence_prediction | we want to get an estimate confidence

by mciniselli Python Version: Current License: No License

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kandi X-RAY | confidence_prediction Summary

confidence_prediction is a Python library. confidence_prediction has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

we want to get an estimate of the confidence of the prediction. The idea is to find a confidence value for the prediction (a sort of probability) to see if RoBERTa is confident on the prediction or not. We hope that if the confidence is high then the predicted code is correct. If this is working we can run the code on a opensource systems and if we find an if condition with high confidence that is different from the one predicted by RoBERTa then this should be a bug. You can find the files in predict_confidence folder.

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confidence_prediction has a low active ecosystem.

It has 0 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

confidence_prediction has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of confidence_prediction is current.

Quality

confidence_prediction has no bugs reported.

Security

confidence_prediction has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

confidence_prediction 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.

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confidence_prediction releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

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

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confidence_prediction Key Features

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confidence_prediction Examples and Code Snippets

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Vulnerabilities

No vulnerabilities reported

Install confidence_prediction

You can download it from GitHub.
You can use confidence_prediction like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

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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