import numpy as np
from math import sqrt
from collections import Counter
class KNNClassifier(object):
"""docstring for KNNClassifier"""
def __init__(self, k):
assert k>=1,"k must be valid"
self.k = k
self._X_train = None
self._y_train = None
def fit(self,X_train,y_train):
'''根据训练数据集X_train和y_train训练KNN分类器'''
self._X_train = X_train
self._y_train = y_train
return self
def predict(self,X_predict):
y_predict = [self._predict(x) for x in X_predict]
return np.array(y_predict)
def _predict(self,x):
distances = [sqrt(np.sum((x_train-x)**2) for x_train in self._X_train)]
nearest = np.argsort(distances)
topK_y=[self._y_train[i] for i in nearest[:self.k]]
votes = Counter(topK_y)
return votes.most_common(1)[0][0]
