Closed slowy07 closed 1 year ago
Implementasi algoritma gradient descent untuk meminimalkan cost hipotesis linier fungsi.
OS : Linux Python: 3.10.9
Linux
3.10.9
parameter variabel:
train_data = ( ((5, 2, 3), 15), ((6, 5, 9), 25), ((11, 12, 13), 41), ((1, 1, 1), 8), ((11, 12, 13), 41), ) test_data = (((515, 22, 13), 555), ((61, 35, 49), 150)) parameter_vector = [2, 4, 1, 5] m = len(train_data) LEARNING_RATE = 0.009
ok sensei @slowy07
close karena pull request sudah di merged
close cause pull request was merged
Description
Implementasi algoritma gradient descent untuk meminimalkan cost hipotesis linier fungsi.
Saya Menggunakan
OS :
Linux
Python:
3.10.9
tambahan lainnya
parameter variabel: