Visual Studio Magazine

Kernel Ridge Regression with Cholesky Inverse Training Using C#

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single ...
Devdiscourse

AI outperforms traditional models in bankruptcy forecasting

Bankruptcy prediction has traditionally relied on statistical approaches such as Altman’s Z-score, which use financial ratios ...
Hosted on MSN

Multiple Linear Regression from Scratch in Python – Simply Explained

Discover a smarter way to grow with Learn with Jay, your trusted source for mastering valuable skills and unlocking your full potential. Whether you're aiming to advance your career, build better ...
Visual Studio Magazine

Linear Regression Using JavaScript

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, ...
Frontiers

Handling missing data of using the XGBoost-based multiple imputation by chained equations regression method

1 Shangwan Coal Mine, Ejin Horo Banner, Ordos, China 2 CCTEG Xi’an Research Institute Co. Ltd., Xi’an, China This study introduces an XGBoost-MICE (Multiple Imputation by Chained Equations) method for ...
Scientific Research Publishing

Dynamic Conditional Feature Screening: A High-Dimensional Feature Selection Method Based on Mutual Information and Regression Error ()

1 School of Mathematics and Statistics, Guilin University of Technology, Guilin, China. 2 Applied Statistics Institute, Guilin University of Technology, Guilin, China.. Current high-dimensional ...
IEEE

An autoML algorithm to select linear regression model and its performance evaluation for linear datasets

Abstract: This paper presents an autoML algorithm to select linear regression model and its performance evaluation for any linear dataset. It computes and compares the performance of various multiple ...
Scientific Research Publishing

Theil, H. (1950) A Rank-Invariant Method of Linear and Polynomial Regression Analysis. Indagationes Mathematicae, 12, 173.

ABSTRACT: In this work, we seek the relationship between the order of the polynomial model and the number of knots and intervals that we need to fit the splines regression model. Regression models ...
Frontiers

Objective quantification of sound sensory attributes in side-by-side vehicles using multiple linear regression models

The evaluation of sound quality is a significant area of research in audio and acoustics (Lyon, 2003). Traditional methods for assessing vehicle sound quality involve both subjective and objective ...