This research work focuses on analyzing the performance of a proposed random forest (RF) method with that of Gaussian Naive Bayes in predicting software problems. The database utilized in this ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the naive Bayes regression technique, where the goal is to predict a single numeric value. Compared to other ...

While the Naïve Bayes algorithm showed less accuracy, it still outperformed random guessing (21). The present study presents a deep learning-based approach for automating the classification of ...

It has been observed that J48 algorithm produced best results as compared to Random Forest and Naïve Bayes algorithms” [7]. J48 is an implementation of the C4.5 decision tree algorithm developed by ...

The prediction model uses the Gaussian Naive Bayes algorithm, which is effective for classification tasks, especially with normally distributed data. Included Files: Naive_Bayes_Classifier.ipynb: A ...

The proposed study performs better than random forest, SVM, and Naive Bayes algorithms in all categories. Hence, this research demonstrates the effectiveness of heuristic-based machine learning in ...

Group 1 was used for training and testing the Gaussian Naive Bayes algorithm, while Group 2 was used for training and testing the novel random forest algorithm. Python and relevant libraries such as ...