When we talk about “linear regression,” what typically comes to mind is Ordinary Least Squares (OLS)—that “best fit” line through data points. OLS is simple and intuitive, but it gives a single, de...

In machine learning regression tasks, we’re always searching for the perfect loss function to guide model learning. The two most common choices are Mean Squared Error (MSE, L2 Loss) and Mean Absolu...

In machine learning, model performance largely depends on the selection of hyperparameters. However, finding the optimal hyperparameter combination—hyperparameter optimization (HPO)—remains a chall...

The State-Adaptive Neuro-Fuzzy Inference System (S-ANFIS) is a simple generalization of the ANFIS network that provides a more flexible framework for modeling complex systems by distinguishing betw...

An adaptive neuro-fuzzy inference system (ANFIS) integrates neural networks and fuzzy logic, first introduced by Jyh-Shing Roger Jang in 1993. It combines the interpretability of fuzzy inference sy...