updated report

This commit is contained in:
Claudio Maggioni 2023-05-31 18:20:34 +02:00
parent 786d6a0684
commit 066c0d0701
2 changed files with 2 additions and 2 deletions

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@ -21,7 +21,7 @@ expected info, you'll be fine.-->
The code and result files, part of this submission, can be found at: The code and result files, part of this submission, can be found at:
- Repository: [https://github.com/infoMA2023/project-02-bug-prediction-maggicl](https://github.com/infoMA2023/project-02-bug-prediction-maggicl) - Repository: [https://github.com/infoMA2023/project-02-bug-prediction-maggicl](https://github.com/infoMA2023/project-02-bug-prediction-maggicl)
- Commit ID: **5f30b3b71b50b28f4c870ff114a760ece1005531** - Commit ID: **786d6a06847b217bdad53804f8a6c79e30134ef3**
# Data Pre-Processing # Data Pre-Processing
@ -429,4 +429,4 @@ classifiers would be useful in predicting potential bugs in the Google JSComp pr
literature presented during lecture, it is not certain if the same trained classifier would yield acceptable results for source literature presented during lecture, it is not certain if the same trained classifier would yield acceptable results for source
code from another project. This is because differences in coding conventions, the bug tracking process, or simply the definition of code from another project. This is because differences in coding conventions, the bug tracking process, or simply the definition of
what constitutes a bug may vary from project to project. A solution to this problem might be to simply train the classifiers on a dataset what constitutes a bug may vary from project to project. A solution to this problem might be to simply train the classifiers on a dataset
coming from the project where bug prediction is needed. coming from the project where bug prediction is needed.

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