Gaussian process classification

Gaussian process classification is a machine learning method used to predict categories or labels for data. It models the underlying relationship between inputs (like features) and outputs (categories) by assuming that related data points have similar labels. Instead of giving definite answers, it provides probabilities, indicating how confident it is in each possible category. Think of it like drawing a smooth, flexible surface over data points, where the surface’s shape helps determine the likelihood of each class for new inputs. This approach is powerful for handling uncertainty and making well-informed predictions in complex, real-world problems.