def linearRegression_Loss(X, t):
    # Max iterations, or step count, for gradient descent
    maxIters = 100
    # Step size, or learning rate
    epsilon = .01

    # Initalize beta to be an array the same size of features of x[i], then set all weights to zero
    beta = np.array(X[i].shape())
    initializeWeights(beta)

    print("Features length: " + len(X[i]))
    print("Weights length: " + len(beta))

    return beta