This repository contains an implementation of the Linear Regression algorithm in JavaScript. Linear Regression is a popular supervised learning algorithm used to model the relationship between dependent and independent variables. It is widely used in various domains, such as finance, economics, and data analysis.
How It Works
The Linear Regression algorithm aims to find the best-fit line that represents the relationship between input features (independent variables) and the target variable (dependent variable). It estimates the coefficients (slope and intercept) of the line that minimizes the sum of squared errors between the predicted and actual values.
The algorithm uses a training dataset with known input features and target values to learn the optimal coefficients. Once the coefficients are determined, they can be used to make predictions on new data points.