Learn With Jay on MSN

Linear regression gradient descent explained simply

Understand what is Linear Regression Gradient Descent in Machine Learning and how it is used. Linear Regression Gradient ...
eLife

On CA1 ripple oscillations in rats and the reassessment of asynchronicity evidence

Ripples maintain time-locked occurrence across the septo-temporal axis and hemispheres while showing local phase coupling, revealing a dual mode of synchrony in CA1 network dynamics.
eLife

Global molecular landscape of early MASLD progression in obesity

The authors provide a useful integrated analytical approach to investigating MASLD focused on diverse multiomic integration methods. The strength of evidence for this new resource is solid, as ...
Scientific Research Publishing

Financial Prediction Models in Banks: Combining Statistical Approaches and Machine Learning Algorithms ()

Felimban, R. (2025) Financial Prediction Models in Banks: Combining Statistical Approaches and Machine Learning Algorithms.
IEEE

Prediction of Wind Power Generation using Novel Linear Regression Algorithm Compared over Lasso Algorithm for Improving Accuracy Rate

Abstract: This paper is a novel approach to improving the accuracy of wind power generation predictions by using linear regression (LR) algorithm differentiated with the Lasso regression (LaR). The ...
Frontiers

Distributed quantile regression over sensor networks via the primal–dual hybrid gradient algorithm

As one of the important statistical methods, quantile regression (QR) extends traditional regression analysis. In QR, various quantiles of the response variable are modeled as linear functions of the ...
GitHub

A scikit-learn compatible implementation of the Adaptive Lasso algorithm for feature selection and regression.

Adaptive Lasso is an extension of the standard Lasso method that provides improved feature selection properties through weighted L1 penalties. It assigns different weights to different coefficients in ...
IEEE

Classification of Fraud Websites using Linear regression Algorithm and Recurrent Neural Network Algorithm with Improved Accuracy

Abstract: The purpose of this work is to improve the detection of fraud websites using Novel Linear Regression Algorithm and Recurrent Neural Network Algorithm. Materials and Methods: Novel Linear ...
Visual Studio Magazine

AdaBoost Regression Using C#

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the AdaBoost.R2 algorithm for regression problems (where the goal is to predict a single numeric value). The ...
Visual Studio Magazine

Simple k-NN Regression Using C#

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of k-nearest neighbors regression to predict a single numeric value. Compared to other machine learning ...