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TaylorFit is a multivariate polynomial regression application that fits data to a predictive model consisting of a polynomial function, such as
f(x, y) = ax + by + cxy
where x, y, and xy are terms selected by the user, and a, b, and c
are coefficients determined using least squares regression.
The application works entirely client-side in your browser, so there's no need to download or install anything and no need to create an account. In order to be reasonably efficient, TaylorFit utilizes specific JavaScript primitives and browser capabilities that emulate native execution.
Architecture - Explains the way different parts of the program interact with each other. Read this before you start implementing.
Installation - Explains how to set up a development environment.
Data Treatment - Discusses the processing of data after it is handed over to the engine. What goes on behind the scenes mathematically.
Engine API -
Docs for interacting with the engine, whether via a web worker's postMessage() or with a WebSocket.