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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 #75
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@rishabh-jain14
rishabh-jain14
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(削除) 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 (削除ここまで)
(追記) 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 (追記ここまで)
Aug 31, 2021
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.
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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