Write a code named as gd. m to implement gradient decent algorithm for the logistic regression problem (1) using the constant step-size scheme. the input for gd. m should include xtr, ytr, yte, yte, the regularization parameter λ, and the constant step-size t. the output for gd. m should be the training error, test error and the objective value at each iteration

Write a function so that the main0 code below can be replaced by the simpler code that calls function mphandminutes tomiles0. original main0 int main) l double milesperhour-70.0; double minutestraveled = 100.0; double hourstraveled; double milestraveled; hourstraveled = minutestraveled / 60.0; milestraveled = hourstraveled * milesperhour; cout < "miles" 2 using namespace std; 4 /* your solution goes here/ 6 int maino 1 test passed 7 double milesperhour 70.0 all tests passed 8 double minutestraveled 100.0; 10 cout < < "miles: " < < mphandminutestomiles(milesper-hour, minutestraveled) < < endl; 12 return 0; 13