IEEE

Predictive Analysis of Network-Based Attacks by Hybrid Machine Learning Algorithms Utilizing Bayesian Optimization, Logistic Regression, and Random Forest Algorithm

Abstract: These days, intrusion detection systems are one of the newest trends in society. These technologies serve as a defense against a variety of security breaches, the number of which has been ...
Fast Company

AI data wars push Reddit to block the Wayback Machine

As the battle to train artificial intelligence models becomes more intense and Reddit’s rich content library becomes more valuable, the social media giant has taken steps to block the Internet Archive ...
Hosted on MSN

Logistic Regression Machine Learning Example ¦ Simply Explained

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...
EdSource

Learning Recovery Emergency Block Grant

Research shows the effectiveness of intensive, individualized instruction, known as high-impact tutoring. Unlike in other states, California districts still have money to pay for it. EdSource · ...
GitHub

Lung Cancer Prediction Project

In this project, we leverage the power of artificial intelligence in healthcare to predict lung cancer risks. By employing various machine learning techniques, we aim to assist medical professionals ...
mwnation

School block project to improve learning space

Minister of Basic and Secondary Education Madalitso Kumbauwa Wirima has commended the Malawi Education Reform Programme (Merp) for constructing decent classroom blocks in primary schools in Mzimba ...
Scientific Research Publishing

Machine Learning-Based Classification of Coronary Heart Disease: A Comparative Analysis of Logistic Regression, Random Forest, and Support Vector Machine Models ()

1 Department of Business Information System, Central Michigan University, Mount Pleasant, MI, USA. 2 Department of MPH, Central Michigan University, Mount Pleasant, MI, USA. 3 Department of ...
Frontiers

Comparison between traditional logistic regression and machine learning for predicting mortality in adult sepsis patients

Background: Sepsis is a life-threatening disease associated with a high mortality rate, emphasizing the need for the exploration of novel models to predict the prognosis of this patient population.