Function run_logistic 

pub fn run_logistic()

Trains and evaluates logistic regression model

High-level training orchestration for binary classification. Automates:

• Training loop with specified learning rate and epochs
• Feature normalization and bias handling (automatic)
• Test set evaluation with accuracy metrics
• Progress reporting every 10 iterations

Arguments

• xy - Data container with training and test sets
• l - Learning rate controlling gradient descent step size
• e - Number of training epochs

Output

Prints:

• Dataset dimensions for verification
• Iteration progress (every 10 steps)
• Total training time
• Classification accuracy on test set

Example

use iron_learn::regression::{XY, run_logistic};

let xy = XY { /* ... */ };
run_logistic(&xy, 0.01, 10000);  // Learning rate 0.01, 10k iterations