Mavzu: Qo’lda yozilgan raqamni aniqlash uchun dataset shakllantirish Bajardi : Ismoilov Temurbek Qabul qildi : Temirov Azizbek tuit 2022-2023 Ishning maqsadi

def Euclidean_distance(row1, row2): distance = 0 for i in range(len(row1)-1): distance += (row1[i] — row2[i])**2 return sqrt(distance)
Eucledian masofasini topib olamiz
def Get_Neighbors(train, test_row, num): distance = list() # [] data = [] for i in train: dist = Euclidean_distance(test_row, i) distance.append(dist) data.append(i) distance = np.array(distance) data = np.array(data) index_dist = distance.argsort() data = data[index_dist] neighbors = data[:num] return neighbors	Masofani tartiblagandan so'ng, k eng yaqin qo'shnilarni olish
def predict_classification(train, test_row, num): Neighbors = Get_Neighbors(train, test_row, num) Classes = [] for i in Neighbors: Classes.append(i[-1]) prediction = max(Classes, key= Classes.count) return prediction	Yangi ma'lumotlar nuqtasi sinfini bashorat qilish
def accuracy(y_true, y_pred): n_correct = 0 for i in range(len(y_true)): if y_true[i] == y_pred[i]: n_correct += 1 acc = n_correct/len(y_true) return acc	Aniqlikni hisoblash Aniqlik o'lchangan qiymatning haqiqiy qiymatga qanchalik yaqinligini ko'rsatadi.
from sklearn.datasets import fetch_openml, load_digits import numpy as np import pandas as pd import matplotlib.pyplot as plt import matplotlib	Kutubxonalarni import qiling
standard format mnist.keys() mnist.target = mnist.target.astype(np.int8) x = np.array(mnist.data) y = np.array(mnist.target) x.shape, y.shape si = np.random.permutation(x.shape[0]) x = x[si] y = y[si]	Ma'lumotlarni oldindan qayta ishlash
some_digit = x[12] some_digit_image = some_digit.reshape(28, 28) plt.imshow(some_digit_image, cmap=matplotlib.cm.binary) plt.axis(“off”) plt.show()	Ma'lumotlarning vizualizatsiyasi
trainx = x[:2000] trainy = y[:2000] train = np.insert(trainx, 784, trainy, axis = 1)prediction = predict_classification(train, train[1244], 4) prediction #Output 8.0	Modelni bashorat qilish

Dastur natijalari.

1. 
   Birinchi qadamimiz yani raqamlarni saqlash jarayonlari
   

2. 
   Raqamlarni alohida chiqish tartibini ko’rsatish
   

3. 
   Bitta belgini tanlash va tahlil qilish
   

4. 
   Raqam chiqishini tahrirlash
   

KNN algoritmi
6 ta berilgan sonlar Ichida eng yaqinini tanlash va taqqoslash

5. 
   Raqamlarni saqlash jarayonlari
   

6. 
   Va yakuniy datasetimizdan foydalanib kiritilgan raqamni olish
   

XULOSA
Ushbu amaliy mashg‘ulot python dasturlash tilida datasetlarni yaratish va ulardan foydalanishni o’rganish maqsadida foydalanildi . Bu topshiriq davomida bir nechta kurubxonalardan foydalanilgan hamda quyidagicha xulosalar va natijalar keltirilgan:
1. Adabiyotlar tahlil qilingan
2. Kiritilgan ,ma’lumotlar asosida dataset shakllantirilgan
3. Datasetdan malumot olish va tekshirish tartibi qo’llanilgan
Foydalanilgan adabiyotlar ro‘yxati
1. https://www.w3schools.com/python/module_statistics.asp
2. https://www.analyticsvidhya.com/blog/2022/04/a-comprehensive-guide-on-pygal-the-next-generation-data-visualization-library-in-python/