Abstract: Multi-linear regression (MLR) algorithm is simple but one of the powerful machine learning algorithms for prediction where output linearly depends on the independent variables. This work ...

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

Electrocardiogram (ECG) reconstruction involves synthesizing leads from a reduced or alternative lead set. While ECG leads are generally considered linearly related, recording distortions and ...

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses the kernel matrix inverse (Cholesky ...

This C library provides efficient implementations of linear regression algorithms, including support for stochastic gradient descent (SGD) and data normalization techniques. It is designed for easy ...

To handle principal component analysis (PCA)-based missing data with high correlation, we propose a novel imputation algorithm to impute missing values, called iterated score regression. The procedure ...

You can create a release to package software, along with release notes and links to binary files, for other people to use. Learn more about releases in our docs.

In this article, we will explore how to implement a simple linear regression model from scratch using Python. The goal of this project is to create a model that predicts a target variable based on ...