Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.

Mr. Currell was a deputy undersecretary and senior adviser at the Department of Education from 2018 to 2021. He is a trustee of Gustavus Adolphus College in St. Peter, Minn. This week, about 200,000 ...

ABSTRACT: This paper introduces a method to develop a common model based on machine learning (ML) that predicts the mechanical behavior of a family with three composite materials. The latter are ...

This cross-sectional study investigated SLD-related variables using decision tree regression in apparently healthy adults. Participants were consecutively recruited from the Health Promotion and Check ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Decision-making during the early stages of research and development (R&D) should be ...

ABSTRACT: We explore the performance of various artificial neural network architectures, including a multilayer perceptron (MLP), Kolmogorov-Arnold network (KAN), LSTM-GRU hybrid recursive neural ...

Balancing water quality standards while facilitating economic growth with uncertain factors in a complex system is challenging for policy makers. This case study analyses the fictional town of Fortuna ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of decision tree regression using the C# language. Unlike most implementations, this one does not use recursion ...

Decision tree regression is a machine learning technique . To predict the output y for an input vector X, the tree structure encodes a set of if-then rules such as, "If the value of X at index [2] is ...