我有7个类别需要分类，并且有10个功能。在这种情况下，我是否需要使用k的最佳值，还是我必须针对1到10(大约10)之间的k值运行KNN，并借助算法本身确定最佳值？
最佳答案
除了我在评论中发布的the article之外，还有this one，它还建议:
Choice of k is very critical – A small value of k means that noise will have a higher influence on the result. A large value make it computationally expensive and kinda defeats the basic philosophy behind KNN (that points that are near might have similar densities or classes ) .A simple approach to select k is set k = n^(1/2).
这将在很大程度上取决于您的具体情况，有时最好遍历k的每个可能值并自行决定。
关于classification - k最近邻算法中k的值，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/11568897/