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x,y=make_blobs(n_samples=500,n_features=2,centers=4,cluster_std=1.5,random_state=4)
y
len(x)
len(y)
plt.style.use('seaborn')
plt.figure(figsize=(10,10))
plt.scatter(x[:,0],x[:,1],c=y,marker='*',s=100,edgecolors='yellow')
plt.show()
x_train,x_test,y_train,y_test=train_test_split(x,y,random_state=0)
knn5=KNeighborsClassifier(n_neighbors=5)
knn1=KNeighborsClassifier(n_neighbors=1)
knn5.fit(x_train,y_train)
knn1.fit(x_train,y_train)
y_pred_5=knn5.predict(x_test)
y_pred_1=knn1.predict(x_test)
from sklearn.metrics import accuracy_score
print("accuracy with k=5", accuracy_score(y_test,y_pred_5)*100)
print("accuracy with k=1", accuracy_score(y_test,y_pred_1)*100)