Linear.LinearRegression

constructor()

This class implements ordinary least squares linear regression. It estimates coefficients for a linear model by minimizing the squared error between predicted and actual values.

Methods

• fit(X: number[][], Y: number[]): void
• predict(X: number[][]): number[]

fit

• X - Feature matrix of shape [nSamples, nFeatures].
• Y - Target values of length nSamples.

predict

• X - Feature matrix for which to compute predictions.

Example

const lr = new LinearRegression();
lr.fit([[0], [1]], [1, 3]);
const pred = lr.predict([[2]]); // about 5