sweptfitted
Sweptfitted is a term used in the context of data analysis and modeling, particularly in the field of statistics and machine learning. It refers to a process where a model or curve is adjusted to fit a set of data points in a way that minimizes the difference between the observed values and the values predicted by the model. The term "swept" implies a systematic and comprehensive application of the fitting process across the entire dataset or a significant portion of it.
The goal of sweptfitting is to find the best possible parameters for a chosen model that describe
The result of a sweptfitting process is a fitted model that can be used for various purposes,