KNN hardcore.py

import numpy as np
from math import sqrt
import matplotlib.pyplot as plt
import warnings
from matplotlib import style
from collections import Counter

style.use('fivethirtyeight')

dataset = {'k':[[1,2],[2,3],[3,1]],'r':[[6,5],[7,7],[8,6]]}
new_features =[5,7]

def k_nearest_neighbors(data,predict,k=3):
    if len(data) >= k:
        warnings.warn('K is set to value less ')
    distances = []
    for group in data:
        for features in data[group]:
            euclidean_distance =np.linalg.norm(np.array(features)-np.array(predict))#check it out
            distances.append([euclidean_distance , group])

    votes = [i[1] for i in sorted(distances)[:k]]
    print(Counter(votes).most_common(1))
    vote_result = Counter(votes).most_common(1)[0][0]
    return vote_result
result = k_nearest_neighbors(dataset,new_features,k=3)
print(result)
[ [plt.scatter(ii[0],ii[1],s=100,color=i) for ii in dataset[i]] for i in dataset]
plt.scatter(new_features[0],new_features[1])
plt.show()