GitHub

sms-spam-classifier

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 ...
Hosted on MSN

Sleep Stage Classification with Python: EEG, Scikit-Learn & MNE

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!
IEEE

Comparative Analysis of the Bernoulli and Multinomial Naive Bayes Classifiers for Text Classification in Machine Learning

Abstract: The purpose of the report is a comparative analysis of the Bernoulli and Multinomial Naive Bayes classifiers in text classification for machine learning. The conducted research demonstrates ...
Hosted on MSN

Build A Neural Network In Python — Multiclass Classification With Softmax

Welcome to Learn with Jay – your go-to channel for mastering new skills and boosting your knowledge! Whether it’s personal development, professional growth, or practical tips, Jay’s got you covered.
Frontiers

Developing a Predictive Model for Depressive Disorders Using Stacking Ensemble and Naive Bayesian Nomogram: Using Samples Representing South Korea

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 ...
IEEE

Laplace Naive Bayes classifier in the classification of text in machine learning

Abstract: The purpose of this publication is to compare the accuracy of a new algorithm based on the Naive Bayesian classifier using the Laplace distribution and named the Laplace Naive Bayes ...
GitHub

spam-classifier

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.