1 unstable release
0.1.0 | Mar 3, 2023 |
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#606 in Science
6KB
52 lines
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