The image Illustrated the Confusion Matrix displays the quantities of true positives (TP), true negatives (TN), false positives (FP), and false negatives (FN) predicted by the pre-trained Naive Bayes model.

The image Illustrated the Confusion Matrix displays the quantities of true positives (TP), true negatives (TN), false positives (FP), and false negatives (FN) predicted by the pre-trained Naive Bayes model.

<p>The rows denote the actual classes, whilst the columns signify the predicted classes. The diagonal elements represent the count of accurate predictions, and the off-diagonal elements denote misclassifications.</p>

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Bibliographic Details
Main Author: Sajid Ullah (8299908) (author)
Other Authors: M. Irfan Uddin (8909933) (author), Muhammad Adnan (678952) (author), Ala Abdulsalam Alarood (21526803) (author), Abdulkream Alsulami (21526806) (author), Safa Habibullah (21526809) (author)
Published: 2025
Subjects:
Genetics
Mental Health
Biological Sciences not elsewhere classified
Information Systems not elsewhere classified
transfer learning approach
proposed approach detects
naive bayes ).
methodology involves developing
machine learning methods
deep learning models
admitted technical debt
software comments associated
create software systems
research &# 8217
previous research focuses
detecting bugs alone
categorising bugs based
software quality assessment
performance evaluation criteria
designated satd examples
software engineering
comparative assessment
software defects
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work presents
without identifying
transformer model
suggested method
software maintenance
slightly lower
significant implications
resource allocation
mozilla firefox
including apache
direct impact
depth exploration
current methodologies
concurrent identification
comprehensive method
business procedures
bug instances
baseline model
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Description
Summary:<p>The rows denote the actual classes, whilst the columns signify the predicted classes. The diagonal elements represent the count of accurate predictions, and the off-diagonal elements denote misclassifications.</p>

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