机器学习算法-KNN

1 KNN 进行分类基于什么 ？
F（x）=
2 k in KNN is a parameter that refer to the number of nearest neighbors to include in the majority voting process
k在KNN中是一个参数，指的是在多数表决过程中要包括的最近的邻居的数量
3 KNN Algorithm is based on feature similarity:choosing the right value of k is a process called parameter tuning, and is important for better accuracy

KNN算法是基于特征相似度的:选择正确的k值是一个称为参数整定的过程，对提高精度非常重要

parameter tuning 参数调优

4 when do we use KNN Algorithm? 我们什么时候使用KNN算法？
we can use knn when {date is labled;data is noise free ;data is small}
对于数据集小的解释是:because KNN is a lazy learner ,so doesn‘t learn a discriminative function from the traing set (因为KNN是一个懒惰的学习者，所以不会从训练集中学习判别函数.对于小的数据集,KNN 是非常好的
)

5 How does KNN Algorithm work?

机器学习算法-KNN

原文：https://www.cnblogs.com/MINGYOUR/p/11819348.html