knn.py

"""
K-nn algorithm 
"""
import numpy as np
from sklearn import datasets
print("This was so confusing to Mr.Jha so he postponed it for later :( ")
print('This is a K-N Algorithm classifier')
iris = datasets.load_iris()
iris_data = iris.data
iris_labels = iris.target
print(iris_data[0], iris_data[79], iris_data[100])
print(iris_labels[0], iris_labels[79], iris_labels[100])
np.random.seed(42)
indices = np.random.permutation(len(iris_data))
n_training_samples = 12
learnset_data = iris_data[indices[:-n_training_samples]]
learnset_labels = iris_labels[indices[:-n_training_samples]]
testset_data = iris_data[indices[-n_training_samples:]]
testset_labels = iris_labels[indices[-n_training_samples:]]
print(learnset_data[:4], learnset_labels[:4])
print(testset_data[:4], testset_labels[:4])
from sklearn.neighbors import KNeighborsClassifier
knn = KNeighborsClassifier()
knn.fit(learnset_data, learnset_labels)
KNeighborsClassifier(algorithm='auto',
                     leaf_size=30,
                     metric='minkowski',
                     metric_params=None,
                     n_jobs=1,
                     n_neighbors=5,
                     p=2,
                     weights='uniform')
print("Predictions form the classifier:")
print(knn.predict(testset_data))
print("Target values:")
print(testset_labels)