TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...
IEEE

Shuffled Linear Regression via Spectral Matching

Abstract: Shuffled linear regression (SLR) seeks to estimate latent features through a linear transformation, complicated by unknown permutations in the measurement dimensions. This problem extends ...
tech2geek

Scikit-learn: The Essential Machine Learning Library for Python

If you’re learning machine learning with Python, chances are you’ll come across Scikit-learn. Often described as “Machine Learning in Python,” Scikit-learn is one of the most widely used open-source ...
GitHub

Full Python/sklearn Adaptation of py-earth

MARS regression is a great and really practical technique. py-earth implemented this, based in the R earth library. The archived state of py-earth means it's only possible to get working with old ...
Hosted on MSN

Linear Regression In Python From Scratch | Simply Explained

Implement Linear Regression in Python from Scratch ! In this video, we will implement linear regression in python from scratch. We will not use any build in models, but we will understand the code ...
C&EN

Simple Linear Regression Models for Prediction of Ionization Energies, Electron Affinities, and Fundamental Gaps of Atoms and Molecules

Chemical Sciences Division, National Institute of Standards and Technology, Gaithersburg, Maryland 20899-8320, United States ...
Frontiers

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

Linear regression models based on parsimonious modeling algorithms of multiple linear regression [Lasso (Tibshirani, 1996) and Elastic-net (Zou and Hastie, 2005)] were used to correlate subjective ...