👉 Curves computing is a mathematical approach that involves the approximation of functions using smooth curves, typically polynomials or splines, to model complex data patterns. This method is particularly useful when dealing with noisy or irregularly sampled data, as it can capture the underlying trends more accurately than traditional linear regression. The process starts with a set of data points and iteratively refines the curve to minimize the difference between the predicted values and the actual data points, often using techniques like least squares optimization. The resulting curve can be used for predictions, interpolation, or visualization, providing a flexible and powerful tool for data analysis and modeling. By balancing smoothness and fidelity to the data, curves computing offers a robust alternative to other methods like polynomial fitting or kernel regression, especially in scenarios where the data exhibits non-linear behavior.
