O‘ZBEKISTON RESPUBLIKASI RAQAMLI TEXNOLOGIYALAR VAZIRLIGI MUHAMMAD AL-XORAZMIY NOMIDAGI
TOSHKENT AXBOROT TEXNOLOGIYALARI UNIVERSITETI
Mashinali o’qitishga kirish
Bajardi: 222-21 guruh talabasi
Abduraxmonov Anvar
TOSHKENT 2023
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier
from sklearn.metrics import accuracy_score
# Ma'lumotlar to'plamini yuklash
# CSV faylni o'qish
df = pd.read_csv('data.csv')
# X va y ni ajratib olish
X = df.drop('xulqi', axis=1)
y = df['xulqi']
# Ma'lumotlarni trening va test qismlarga ajratib olish
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
# KNN modelini yaratish va o'qitish
knn = KNeighborsClassifier(n_neighbors=3) # N tezlik
knn.fit(X_train, y_train)
# Test qismi uchun taxmin qilish
y_pred = knn.predict(X_test)
# Natijalarni baholash
accuracy = accuracy_score(y_test, y_pred)
print(f"Aniqlik: {accuracy}")
# Grafikni chiqarish
fig, ax = plt.subplots()
# O'zgaruvchilarni o'zgartiring, agar x va y larni o'zgartirmoqchi bo'lsangiz
x = df['o`rtacha_baholari']
y = df['sinfi']
# Joriy va to'g'ri natijalarni vizualizatsiya qilish
ax.scatter(x[y == 0], y[y == 0], color='red', label='Xulqi=0')
ax.scatter(x[y == 1], y[y == 1], color='blue', label='Xulqi=1')
ax.set_xlabel('O`rtacha Baholari')
ax.set_ylabel('Sinfi')
ax.legend()
plt.show()
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
from sklearn.svm import SVC
from sklearn.metrics import accuracy_score
# Ma'lumotlar to'plamini yuklash
# CSV faylni o'qish
df = pd.read_csv('data.csv')
# X va y ni ajratib olish
X = df.drop('xulqi', axis=1)
y = df['xulqi']
# Ma'lumotlarni trening va test qismlarga ajratib olish
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
# KNN modelini yaratish va o'qitish
cvm = SVC(kernel='linear',C=1) # N tezlik
cvm.fit(X_train, y_train)
# Test qismi uchun taxmin qilish
y_pred = cvm.predict(X_test)
# Natijalarni baholash
accuracy = accuracy_score(y_test, y_pred)
print(f"Aniqlik: {accuracy}")
# Grafikni chiqarish
fig, ax = plt.subplots()
# O'zgaruvchilarni o'zgartiring, agar x va y larni o'zgartirmoqchi bo'lsangiz
x = df['o`rtacha_baholari']
y = df['sinfi']
# Joriy va to'g'ri natijalarni vizualizatsiya qilish
ax.scatter(x[y == 0], y[y == 0], color='red', label='Xulqi=0')
ax.scatter(x[y == 1], y[y == 1], color='blue', label='Xulqi=1')
ax.set_xlabel('O`rtacha Baholari')
ax.set_ylabel('Sinfi')
ax.legend()
plt.title('CVM')
plt.show()
|
