Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...

Interpretability of Support Vector Machine (SVM) or Neural Networks (NN) models, examples of black-box models, is a field of study that has recently gained attention, especially for the significant ...

Choosing the right curve fit model is essential for revealing key data features, such as rate of change, asymptotes, and EC 50 /IC 50 values. The best model is the one that most faithfully reflects ...

The social model of disability frames disability as something that is created by society, rather than only by medical conditions or physical differences. The model acknowledges that people have ...

This project implements a quadratic nonlinear regression model to estimate the real-world distance between a hand and a camera based on the relative positions of hand landmarks in 2D images. The ...

What is linear regression in machine learning ? Understanding Linear Regression in machine learning is considered as the basis or foundation in machine learning. In this video, we will learn what is ...

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 ...

Abstract: Functional data analysis (FDA) in which each data sample is a function rather than a vector or a matrix has attracted a lot of attention in the statistics community in recent years. However, ...

ABSTRACT: Benzimidazolyl-Chalcones (BZCs) possess nitrogen heteroatoms making them very active molecules when protonated. In this work we will focus on a series of fourteen (14) substituted BZC ...