EurekAlert!

Learning to be simple: machine learning uncovers structures in finite simple groups

A research team of mathematicians and computer scientists has used machine learning to reveal new mathematical structure ...
marktechpost

How to Build an End-to-End Data Engineering and Machine Learning Pipeline with Apache Spark and PySpark

In this tutorial, we explore how to harness Apache Spark’s techniques using PySpark directly in Google Colab. We begin by setting up a local Spark session, then progressively move through ...
Scientific Research Publishing

James, G., Witten, D., Hastie, T., Tibshirani, R., & Taylor, J. (2023). Linear Regression. In G. James, D. Witten, T. Hastie, R. Tibshirani, & J. Taylor (Eds.), An Introduction ...

ABSTRACT: Nowadays, understanding and predicting revenue trends is highly competitive, in the food and beverage industry. It can be difficult to determine which aspects of everyday operations have the ...
Hosted on MSN

Linear Regression Cost Function | Machine Learning | Explained Simply

Learn what is Linear Regression Cost Function in Machine Learning and how it is used. Linear Regression Cost function in Machine Learning is "error" representation between actual value and model ...
Hosted on MSN

Linear Regression Gradient Descent ¦ Machine Learning ¦ Explained Simply

Understand what is Linear Regression Gradient Descent in Machine Learning and how it is used. Linear Regression Gradient Descent is an algorithm we use to minimize the cost function value, so as to ...
BMJ

Accuracy of machine learning methods in predicting prognosis of patients with psychotic spectrum disorders: a systematic review

3 Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 4 Yong Loo Lin School of Medicine, National University of Singapore, Singapore 5 ...
IEEE

Systematic Bias of Machine Learning Regression Models and Correction

Abstract: Machine learning models for continuous outcomes often yield systematically biased predictions, particularly for values that largely deviate from the mean. Specifically, predictions for large ...
Frontiers

Machine learning-based spirometry reference values for the Iranian population: a cross-sectional study from the Shahedieh PERSIAN cohort

Objective: This study aimed to determine spirometric norm values for the healthy Iranian adult population and compare them with established norm equations, specifically the GLI-Caucasian and Iranian ...
IEEE

Magneto Inductive (MI) Channel Variables Prediction Through Machine Learning Linear Regression Method, for Underwater and Underground WSNs

Abstract: In today’s digital era, where information flows seamlessly and is readily available and accessible. However, these information and communication systems are highly dependent on the ...