To evaluate the clinical effectiveness of a Bayesian-based anti-scalping mechanism integrated into a hospital appointment system in improving fairness, efficiency, and patient accessibility while ...
Telecom Fraud Detection: SMS Spam Classifier built with Python, Scikit-learn, and Streamlit. Achieves ~98% accuracy using TF-IDF + Naive Bayes. Includes EDA, fraud trend visualization, and real-time ...
Explore the first part of our series on sleep stage classification using Python, EEG data, and powerful libraries like Sklearn and MNE. Perfect for data scientists and neuroscience enthusiasts!
Abstract: Effective classification of Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) conditions is essential for optimizing communication performance in UAV-assisted networks, where signal quality, ...
Abstract: The transmission line is the most important component of the power system. Classifying the faults occurring on the transmission line helps the system operator activate the mechanism of ...
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This study provided baseline data for preventing depression in female older adults living alone by understanding the degree of their depressive disorders and factors affecting these depressive ...
A Naive Bayes spam/ham classifier based on Bayes' Theorem. A bunch of emails is first used to train the classifier and then a previously unseen record is fed to predict the output.
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