IEEE

Analysis of Neural Network Algorithm in Comparison to Multiple Linear Regression and Random Forest Algorithm

Abstract: Regression analysis, a stalwart in statistical methodology, offers a robust framework for predicting outcomes based on historical data. It hinges on the premise that by scrutinizing past ...
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 ...
Frontiers

Using short-read 16S rRNA sequencing of multiple variable regions to generate high-quality results to a species level

Introduction: Short-read amplicon sequencing studies have typically focused on 1-2 variable regions of the 16S rRNA gene. Species-level resolution is limited in these studies, as each variable region ...
GitHub

Multiple Linear Regression in Statsmodels

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 ...
C&EN

Application of Multiple Linear Regression Models in Deriving Water Quality Criteria for Lead: Comparison of Metal Bioavailability Estimation Approaches

State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China ...
IEEE

An Analysis on Cost and Income Prediction System Using Multiple Linear Regression and Business Intelligence for Entrepreneur in Fruit Crop

Abstract: This paper presents a cost and income forecast system that includes multiple linear regression models and business intelligence (BI) tools and is tailored particularly for fruit crop ...