Discover how econometricians use math and statistics to analyze and predict economic trends, serving in finance and academia ...

Autonomous vehicles could dramatically reduce traffic accidents and injuries on U.S. roads. Drawing on historical data and ...

Objective To analyse temporal trends of respiratory infectious diseases (RIDs) in Baiyin City from 2014 to 2023, aiming to explore the epidemiological patterns of these diseases (tuberculosis, scarlet ...

A Flask-based REST API for managing personal finances with SQLite database, statistical analysis, and income forecasting using linear regression.

ABSTRACT: Nowadays, understanding and predicting revenue trends is highly competitive, in the food and beverage industry. It can be difficult to determine which aspects of everyday operations have the ...

I have successfully run the deep learning models. However, when I run the Gradient Boosting Regression model, the predictions collapse into a straight flat line. I would like to understand why this ...

Abstract: In this age of digital information, theoretical data generation has grown to a level that no person can handle. Thus, several machine learning models are available. Therefore, our aim is to ...

ABSTRACT: Groundwater recharge (GR) is one of the most important processes of the hydrologic cycle, especially in urbanizing regions where land use and climate variability are interacting in a very ...

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, ...

The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict an employee's salary based on age, height, years of experience, and so on ...

Management of water resources is a universal challenge, transcending geographical boundaries. It has been in the limelight for decades due to climate and environmental changes at the global level. The ...