The adjusted r-squared is helpful for multiple regression and corrects for erroneous regression, giving you a more accurate ...

I 'm a big fan of Python for data analysis, but even I get curious about what else is available. R has long been the go-to ...

Wang, Z. (2025) Research on Prediction of Air Quality CO Concentration Based on Python Machine Learning. Advances in Internet ...

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 ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with two-way interactions between predictor variables. Standard linear regression predicts a single numeric value ...

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 ...

This article presents a detailed analysis of an undergraduate physics laboratory experiment designed to determine the density of water using fundamental measurement techniques and data analysis ...

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, ...

Oscillation is becoming one of the most critical issue in a power system with large-scale renewable integration. Frequency-coupled admittance model (FCAM) is widely used in the analysis of ...

Since this part of the course focuses on simple linear regression, you want to check for any linear relationships among variables in the dataframe. You can do this by creating scatterplots using any ...

The study investigates the competency assessment outcome of AI-driven training, student engagement, and demographic factors. Previous studies have examined these factors individually, but this ...