Mastering accurate spatial planting and distribution status of the crops is significantly important for the nation to guide the agricultural production and formulate agricultural policies from a macro ...

Abstract: In this paper, we propose an in-node microprocessor-based vehicle classification approach to analyze and determine the types of vehicles passing over a 3-axis magnetometer sensor. Our ...

Abstract: Machine learning (ML) has been instrumental in solving complex problems and significantly advancing different areas of our lives. Decision tree-based methods have gained significant ...

Mellon, J., and Worrell, C., 2023: Explainability in Cybersecurity Data Science. Software Engineering Institute blog, Accessed July 1, 2026, https://doi.org/10.58012 ...

This article provides a birds-eye view on the role of decision trees in machine learning and data science over roughly four decades. It sketches the evolution of decision tree research over the years, ...

Machine learning holds the potential to solve many real-world problems, but interpretability is a necessary prerequisite for practitioners in high-stakes domains such as medicine and law. Decision ...

Data Science expert with desire to help companies advance by applying AI for process improvements. The journey to Kaggle’s winning approach started in the mid-20th century, and its development has ...