18CSL76 Implement k-Nearest neighbour algorithm.

 Write a program to implement a k-Nearest Neighbour algorithm to classify the iris data set. Print both correct and wrong predictions. Java/Python ML library classes can be used for this problem.

from sklearn.model_selection import train_test_split from sklearn.neighbors import KNeighborsClassifier from sklearn.metrics import classification_report, confusion_matrix from sklearn import datasets iris=datasets.load_iris() iris_data=iris.data iris_labels=iris.target print(iris_data) print(iris_labels) x_train, x_test, y_train, y_test=train_test_split(iris_data,iris_labels,test_size=0.30) classifier=KNeighborsClassifier(n_neighbors=5) classifier.fit(x_train,y_train) y_pred=classifier.predict(x_test) print('confusion matrix is as follows') print(confusion_matrix(y_test,y_pred)) print('Accuracy metrics') print(classification_report(y_test,y_pred))