Abstract: The conventional multiple linear regression model is limited by its inability to process high-dimensional datasets, susceptibility to multicollinearity, and challenges in modeling non-linear ...

School of Computing and Engineering, University of West, London, UK. In recent years, inflation has been a worrying factor for every country, which has become particularly high due to various ...

ABSTRACT: Accurate forecasting of the system marginal price (SMP) is crucial to improve demand-side management and optimize power generation scheduling. However, predicting the SMP is challenging due ...

Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...

In this video, we will implement Multiple Linear Regression in Python from Scratch on a Real World House Price dataset. We will not use built-in model, but we will make our own model. This can be a ...

This lesson will be more of a code-along, where you'll walk through a multiple linear regression model using both statsmodels and scikit-learn. Recall the initial regression model presented. It ...

Background: The aim of the present study was to establish a predictive model to predict the peritoneal cancer index (PCI) preoperatively in patients with pseudomyxoma peritonei (PMP). Conclusion: This ...

Abstract: This paper focuses on a multidimensional indicator prediction assessment method based on time series and multiple linear regression modelling. Through in-depth analysis of relevant data, ...