goml

README

goml

goml is a lightweight machine learning library implemented in Golang. Currently, it provides regression algorithms, and the aim is to expand its capabilities to include various machine learning algorithms in the future.

Installation

To use goml in your Golang project, simply download it as follows:

go get github.com/ezrantn/goml

Regression Algorithms

Simple Linear Regression

Function: CalculateSlope

func CalculateSlope(x []float64, meanX float64, y []float64, meanY float64) float64

Calculates the slope of the regression line for simple linear regression.

Parameters:

• x: Input feature values.
• meanX: Mean of the input feature values.
• y: Output values.
• meanY: Mean of the output values.

Returns:

• The slope of the regression line.

Function: Mean

func Mean(data []float64) float64

Calculates the mean of a given slice of float64 values.

Parameters:

• data: Slice of float64 values.

Returns:

• The mean of the input data.

Example Usage

package main

import (
   "fmt"
   "github.com/thisdoraemon/goml"
)

func main() {
   // Example data
   x := []float64{1, 2, 3, 4, 5}
   y := []float64{2, 4, 5, 4, 5}

   // Calculate means
   meanX := goml.Mean(x)
   meanY := goml.Mean(y)

   // Calculate slope
   slope := goml.CalculateSlope(x, meanX, y, meanY)

   // Display result
   fmt.Printf("Slope: %.2f\n", slope)
}

Contribution

Feel free to contribute to goml by submitting issues, feature requests, or pull requests. Your contributions are highly appreciated.

License

This project is licensed under the GNU GENERAL PUBLIC LICENSE - see the LICENSE file for details.