Linear-Regression-ML

Linear regression algorithm that predicts future values depending on existing data

use linear_regression::{linear_regression, predict}

fn main() {
  /* Some data */
  let data: Vec<(f32, f32)> = vec![
    (17.9, 2013.0),
    (17.63, 2014.0),
    (14.95, 2015.0),
    (15.14, 2016.0),
    (16.24, 2017.0),
    (17.6, 2018.0),
    (17.47, 2019.0),
    (15.84, 2020.0),
    (18.7, 2021.0)
  ];

  for price in &data {
      println!("Year: {}, GDP = ${:.3}B", price.1, price.0);
  }

  // Linear regression prints the equation and returns k and b
  let eq = linear_regression(&data);

  // Test cases for different x values
  predict(&eq, 2022.0);
}

Example:

Vertices data: [
(0.0, 2.1),
(1.0, 1.92),
(2.0, 1.84),
(3.0, 1.71),
(4.0, 1.64)
]
Regression line: y = -0.113x + 2.068

Predicted value for 5.000 is 1.503
Predicted value for 6.000 is 1.390
Predicted value for 7.000 is 1.277
Predicted value for 8.000 is 1.164
Predicted value for 9.000 is 1.051

linear-regression 0.1.0

Linear-Regression-ML