KNN

#KNN

from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier
from sklearn.metrics import confusion_matrix, accuracy_score, classification_report
from sklearn.datasets import load_iris

data = load_iris()
X = data.data
y = data.target

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state = 42)

scaler = StandardScaler()
X_train = scaler.fit_transform(X_train)
X_test = scaler.fit_transform(X_test)


knn = KNeighborsClassifier(n_neighbors = 5)
knn.fit(X_train, y_train)

y_pred = knn.predict(X_test)


accuracy = accuracy_score(y_test, y_pred)
conf = confusion_matrix(y_test, y_pred)
classR = classification_report(y_test, y_pred)

print(accuracy)
print(conf)
print(classR)