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>

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Sajid Ullah (8299908) (author)
مؤلفون آخرون:	M. Irfan Uddin (8909933) (author), Muhammad Adnan (678952) (author), Ala Abdulsalam Alarood (21526803) (author), Abdulkream Alsulami (21526806) (author), Safa Habibullah (21526809) (author)
منشور في:	2025
الموضوعات:	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 xlink "> 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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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.

مواد مشابهة