In response to Issue #67: Naive Bayes Classifier added along with a unit testing file; also, included a test_use_cases.py file to compare the accuracy of naive bayes models using both numpy-ml and scikit-learn using dataset in the file wine.data#75
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rishabh-jain14 wants to merge 1 commit intoddbourgin:masterfrom
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In response to Issue #67: Naive Bayes Classifier added along with a unit testing file; also, included a test_use_cases.py file to compare the accuracy of naive bayes models using both numpy-ml and scikit-learn using dataset in the file wine.data#75rishabh-jain14 wants to merge 1 commit intoddbourgin:masterfrom
rishabh-jain14 wants to merge 1 commit intoddbourgin:masterfrom
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Hi Rishabh, thanks for the PR, and sorry for my delayed response. Also apologies for not closing issue #67 after @sfsf9797 's PR. I suspect this may have created some confusion :-/ Can you explain what your code adds over the existing implementation? I haven't gone through it in detail, but given that there already exists a validated Gaussian naive Bayes model in the repo, I'm inclined to leave things as they are unless there is significant added functionality. |
Author
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Hey David, thanks for the response.
The PR focuses on the implementation and comparison of the Gaussian Naive
Bayes Classifier using the NumPy-ml repo as well as the scikit-learn
library.
I had realized that the repo already contains a code for the Gaussian naive
Bayes model but as per the issue mentioned #67, it required a brief coded
file that focused on the comparison of the performance of the model in
comparison to the already specified scikit-learn model. So, we can say that
the comparison part is the significant added functionality here.
Feel free to include the PR into the repo if you'd like. I enjoyed
assessing the entire repository and look forward to contributing as much as
I can. :-)
*Rishabh Jain*
…On Thu, Sep 23, 2021 at 9:04 PM David Bourgin ***@***.***> wrote:
Hi Rishabh, thanks for the PR, and sorry for my delayed response. Also
apologies for not closing issue #67
<#67> after @sfsf9797
<https://github.com/sfsf9797> 's PR. I suspect this may have created some
confusion :-/
Can you explain what your code adds over the existing implementation? I
haven't gone through it in detail, but given that there already exists a
validated Gaussian naive Bayes model in the repo, I'm inclined to leave
things as they are unless there is significant added functionality.
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