Preprocess in linear regression

lin_reg_preproc.rs

// Read input data 
let ifile = "FULLPATHTODATASET";
let mut input_data = read_housing_csv(&ifile);

// data preprocessing: train test split 
// define the length of the test data 
let test_chunk_size: f64 = input_data.len() as f64 * 0.3; // we are taking the 30% as test data
// as cast between types 
let test_chunk_size = test_chunk_size.round() as usize;
// split 
let (test, train) = input_data.split_at(test_chunk_size); 
// impressively, rust vectors have split_at attribute
//https://doc.rust-lang.org/std/primitive.slice.html#method.split_at
let train_size = train.len() ; 
let test_size = test.len();
// define the training and target variables 
// to return train and target variables use a simple flat map 
let x_train: Vec<f64> = train.iter().flat_map(|row| row.train_features()).collect();
let y_train: Vec<f64> = train.iter().map(|row| row.train_target()).collect();
// same for test
let x_test: Vec<f64> = test.iter().flat_map(|row| row.train_features()).collect();
let y_test: Vec<f64> = test.iter().map(|row| row.train_target()).collect();

// now as an input linregressionwants a matrix and a vector for y so 
let x_train_matrix = Matrix::new(train_size, 13, x_train); // 13 is the number of features
let y_train_vector = Vector::new(y_train);
let x_test_matrix = Matrix::new(test_size, 13, x_test);