How-To Geek on MSN

How to run R-style linear regressions in Python the easy way

If you have experience with R or want a quick way to generate a regression with statsmodels using a pandas DataFrame, you can ...
Hackaday

Making Math Less Stressful With A Python Super-Calculator

In a recent write-up, [David Delony] explains how he built a Wolfram Mathematica-like engine with Python. Core to the system is SymPy for symbolic math support. [David] said being able to work ...
IEEE

Efficient Algorithms for Estimating the Parameters of Mixed Linear Regression Models

Abstract: Mixed linear regression (MLR) models nonlinear data as a mixture of linear components. When noise is Gaussian, the Expectation-Maximization (EM) algorithm is commonly used for maximum ...
Devdiscourse

AI-powered forecasting boosts retail efficiency: LSTM outshines traditional models

Demand forecasting remains one of the most complex challenges in retail management. As consumer behavior evolves rapidly, ...
Visual Studio Magazine

Implementing k-Nearest Neighbors Regression Using JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of k-nearest neighbors regression using JavaScript. There are many machine learning regression techniques, but k-nearest neighbors is ...
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 ...
Scientific Research Publishing

Hastie, T., Tibshirani, R. and Friedman, J. (2008) The Elements of Statistical Learning: Data Mining, Inference, and Prediction. 2nd Edition, Springer.

ABSTRACT: 1st cases of COVID-19 were reported in March 2020 in Bangladesh and rapidly increased daily. So many steps were taken by the Bangladesh government to reduce the outbreak of COVID-19, such as ...