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The code base is empty #1

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SheryMo opened this issue Dec 19, 2023 · 7 comments
Open

The code base is empty #1

SheryMo opened this issue Dec 19, 2023 · 7 comments

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@SheryMo
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SheryMo commented Dec 19, 2023

Hi mvisionai,

Interesting work, could you please share the code soon?

Thanks

@mvisionai
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Thank you for your interest, SheryMo! The code base has been uploaded.

Please feel free to reach out if you have any questions or need further assistance.

@GURPREET-WEB
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Dear authors,
Thanks for the exciting work.
Please share the complete code; some modules are not there.
Thankyou.
Screenshot 2024-05-23 at 10 11 42 AM

@mvisionai
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Owner

Dear authors, Thanks for the exciting work. Please share the complete code; some modules are not there. Thankyou. Screenshot 2024-05-23 at 10 11 42 AM

Dear GURPREET-WEB,

Thank you for your interest in our project and for reporting the issue you encountered. We apologize for the inconvenience caused by the missing modules.

You can install the metric-learn module using:

pip install metric-learn

We appreciate you taking the time to bring this issue to our attention. If you continue to experience any problems or have any further questions, please don't hesitate to reach out to us.

@GURPREET-WEB
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GURPREET-WEB commented May 27, 2024

Dear mvisionai,
Thank you so much for resolving my query, it's just a Python module, I was not aware of.
Wish you all the best for your future work.
Thanks.

@GURPREET-WEB
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Dear authors,
Thanks for your efforts.
I read your recent paper published in Information Processing and management, named as "A reliable adaptive prototype-based learning for evolving data streams with limited labels".
Could you please provide its codebases for a better understanding of the proposed approach?
Thanks.

@mvisionai
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Dear authors, Thanks for your efforts. I read your recent paper published in Information Processing and management, named as "A reliable adaptive prototype-based learning for evolving data streams with limited labels". Could you please provide its codebases for a better understanding of the proposed approach? Thanks.

Dear GURPREET-WEB,

Thank you for your request and for your interest in our recent paper published in Information Processing and Management, titled "A Reliable Adaptive Prototype-Based Learning for Evolving Data Streams with Limited Labels."

We appreciate your enthusiasm for understanding our proposed approach in greater detail. The codebase will be added to the following GitHub repository: https://github.com/SalahuddinSwati. Please follow this repository for updates.

If you have any questions, please do not hesitate to contact.

@GURPREET-WEB
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Thank you so much @mvisionai, I will keep an eye on the shared repository to see updates. I admire your work in the field of streaming data classification. Wish you all the best for your future work. Thanks.

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