Added Project and Report

project/utilities/dataset.jl

@@ -0,0 +1,42 @@
+using CSV
+using DataFrames
+using LinearAlgebra
+
+@doc raw"""
+    get_dataset(file_path::String, lambda::Float64)
+
+Reads the ML-CUP-23/24 dataset from the given file path and returns the
+necessary matrices and vectors to solve the problem. The LS problem is
+solved with the standard solver in Julia.
+
+### Input
+
+- 'file_path' -- the path to the dataset file.
+- 'lambda' -- the regularization parameter.
+
+### Output
+
+A tuple containing
+
+- 'X_hat' -- the augmented matrix X.
+- 'y_hat' -- the augmented vector y.
+- 'start' -- the initial starting point.
+- 'w_star' -- the optimal solution.
+
+"""
+function get_dataset(filePath::String, λ::Real)
+    X = CSV.File(filePath; header=false) |> DataFrame
+    X = Matrix(X)
+
+    m, n = size(X)
+    X_hat = [transpose(X); λ .* I(m)]
+    y_hat = [(rand(n).*2 .-1); zeros(m)]
+
+    # initial starting point 
+    start = ones(m)
+
+    # w_star is the optimal solution provided by the julia solver 
+    w_star = X_hat \ y_hat
+
+    return X_hat, y_hat, start, w_star
+end