# Linear-Regression-ML
Linear regression algorithm that predicts future values depending on existing data
<br/>

```
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: [  
  &nbsp;(0.0, 2.1),  
  &nbsp;(1.0, 1.92),  
  &nbsp;(2.0, 1.84),  
  &nbsp;(3.0, 1.71),  
  &nbsp;(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