Trained on historical consumption data spanning a decade, the model demonstrated strong predictive performance. It achieved a training error of 0.182 and a forecasting accuracy of 95.2 percent, ...

Computer vision systems combined with machine learning techniques have demonstrated success as alternatives to empirical methods for classification and selection. This study aimed to classify tomatoes ...

Abstract: Because of their transparency, interpretability, and efficiency in classification tasks, decision tree algorithms are the foundation of many Business Intelligence (BI) and Analytics ...

Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., ...

ABSTRACT: The advent of the internet, as we all know, has brought about a significant change in human interaction and business operations around the world; yet, this evolution has also been marked by ...

The ML Algorithm Selector is an interactive desktop application built with Python and Tkinter. It guides users through a decision-making process to identify suitable machine learning algorithms for ...

Java is not the first language most programmers think of when they start projects involving artificial intelligence (AI) and machine learning (ML). Many turn first to Python because of the large ...

Municipal Solid Waste Generation (MSWG) presents a significant challenge for sustainable urban development, with waste production escalating at alarming rates worldwide. To address this issue, ...

Artificial intelligence (AI) has become a cornerstone of modern business operations, driving efficiencies and delivering insights across various sectors. However, as AI systems become more ...