About
This library can make predictions about data using a technique called polynomial regression.
Polynomial regression uses a technique called Gaussian-Jordan elimination, which creates a predictive model that more accurately fits non-linear data.
How to use
Let's say you have your typical cartesian coordinates (x and y coordinates)
const data = x : 5 y : 8 x : 9 y : 12 // and so on...;
This library will read this data, and then make a prediction about a y value, given an x.
//This library is a UMD module (thanks webpack!); //Factory function - returns a PolynomialRegression instance. 2nd argument is the degree of the desired polynomial equation.const model = PolynomialRegression;//terms is a list of coefficients for a polynomial equation. We'll feed these to predict y so that we don't have to re-compute them for every prediction.const terms = model;//10 is just an example of an x value, the second argument is the independent variable being predicted.const prediction = model;
That's it! I've created an example using random data in the example folder of this repo. Please use the issues section to communicate any bugs, questions, or feature requests.