Simple Linear Regression with Go

This project provides an implementation of linear regression with two variables in Go. It includes various evaluation metrics such as R² (R-squared), Mean Squared Error (MSE),and Mean Absolute Error (MAE).

Features

• Load data from a CSV file
• Fit a linear regression model
• Calculate MAE, MSE, and R²
• Make predictions based on the model

Getting Started

Usage

1. go get github.com/BlueGob/Linear-regression-Go

2. Create a Go file (main.go) with the following content:

   package main
   
   import (
       "fmt"
       "github.com/BlueGob/Linear-regression-Go/regression"
   )
   
   func main() {
       lr := regression.NewLinearRegression("employee_salary.csv", "Salary", 0.2)
       lr.Fit()
       fmt.Println("Prediction for input 2:", lr.Predict(2))
       fmt.Println("Mean Absolute Error (MAE):", lr.Mae())
       fmt.Println("Mean Squared Error (MSE):", lr.Mse())
       fmt.Println("R-squared (R²):", lr.R2())
   }

3. Run the program:

   go run main.go

Dataset

The dataset used for this project can be found on Kaggle