IIT Guwahati has released the Data Science & Artificial Intelligence subject this year. Download the GATE Data Science & ...

Objective Certain leading medical organisations are considering alternatives to the Body Mass Index (BMI) as a predictor of the risk for non-communicable chronic disease (NCD) or death. Our objective ...

Introduction The Sport Mental Health Assessment Tool-1 (SMHAT-1) was developed to screen elite athletes for mental health concerns. Previous work demonstrated high false negative rates (FNRs) for the ...

This paper would be of interest to researchers studying cognitive control and adaptive behavior, if the concerns raised in the reviews can be addressed satisfactorily. Understanding how task knowledge ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with two-way interactions between predictor variables. Standard linear regression predicts a single numeric value ...

Attendance is expected in all live lectures. Valid excuses for absence with permission will be accepted with documentation, but students are required to watch the lecture videos and submit class ...

Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...

This project predicts placement salary (LPA) based on CGPA and IQ using Single, Multiple, and Polynomial Linear Regression models. It includes manual and sklearn implementations for comparison.

Linear regression may be the most basic and accessible machine learning (ML) algorithm, but it’s also one of the fastest and most powerful. As a result, professionals in business, science, and ...

Presenting an algorithm that solves linear systems with sparse coefficient matrices asymptotically faster than matrix multiplication for any ω > 2. Our algorithm can be viewed as an efficient, ...