Struct Nabla

pub struct Nabla;

Nabla is where all the magic happens and where all the gradients are calculated.

Implementations

impl Nabla

Calculates the gradients (nabla) for linear regression with multiple features

Arguments

• X - The input feature matrix as an NDArray
• y - The actual target values as an NDArray
• y_pred - The predicted values as an NDArray
• N - The number of samples

Returns

A vector containing the gradients for each parameter, including intercept

pub fn linear_regression_gradients( X: &NDArray, y: &NDArray, y_pred: &NDArray, N: usize, ) -> Vec<f64>

impl Nabla

pub fn linear_regression( X: &NDArray, y: &NDArray, alpha: f64, epochs: usize, ) -> (Vec<f64>, Vec<f64>)

Performs linear regression using gradient descent with multiple features

Arguments

• X - The input feature matrix as an NDArray.
• y - The output target as an NDArray.
• alpha - The learning rate.
• epochs - The number of iterations for gradient descent.

Returns

A tuple containing the optimized parameters and the history of MSE for each epoch.