Machine Learning : A Comprehensive, Step-by-Step Guide to Learning and Applying Advanced Concepts and Techniques in Machine Learning by PETER BRADLEY

Author:PETER BRADLEY [BRADLEY, PETER]
Language: eng
Format: azw3
Published: 2018-12-31T16:00:00+00:00

import numpy as np

import matplotlib.pyplot as plt

from matplotlib import style

import warnings

from collections import Counter

#dont forget this

import pandas as pd

import random

style.use('fivethirtyeight')

def k_nearest_neighbors(data, predict, k=3):

if len(data) >= k:

warnings.warn('K is set to a value less than total voting groups!')

distances = []

for group in data:

for features in data[group]:

euclidean_distance = np.linalg.norm(np.array(features)-np.array(predict))

distances.append([euclidean_distance,group])

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