|
Grux talabasi Qo`narov Shohrux Mashinali o'qitishga kirish fanidan
|
tarix | 08.05.2023 | ölçüsü | 464,4 Kb. | | #109064 |
| mashinali o`qitish 1
213-20 grux talabasi
Qo`narov Shohrux
Mashinali o'qitishga kirish fanidan
1-Amaliy mashg`ulot.
1. Chiziqli regressiya tushunchasi. y=wx funksiyadagi Gradient (og`irlik) qiymatini topish. Gradient pastlash grafigi va Loss grafigini xosil qilish.
import numpy as np
import matplotlib.pyplot as plt
import math
x = [1,2,3]
y = [2,4,6]
r = np.zeros(5)
for w in range(0,5):
loss = 0
for j in range(0,3):
loss =loss + (w*x[j]-y[j])*(w*x[j]-y[j])
r[w]= loss/3
print(f'r[{w}]=',r[w])
2. Ikkinchi darajali polynomial regressiya tushunchasi. y=w1x 2+w2x noma’lum koeffitsientlarni toppish. Loss grafigini chiqarish.
import numpy as np
import matplotlib.pyplot as plt
import math
n = int (input('signal soni = '))
m = int(input('testlaw qiymati = '))
x = [1,2,3]
y = [2,4,6]
w = np.zeros(n)
r = np.zeros(n)
w[0]=4
a = 0.01
for i in range(1,n):
for j in range(0,3):
w[i]=w[i-1]-a*2*(w[i-1]*x[j]-y[j])*x[j]
r[i-1]=(w[i-1]*x[j]-y[j])**2
if 0.001z= w[i-1]*m
print(z)
plt.plot(r)
plt.show()
Dostları ilə paylaş: |
|
|