首页 / 更多教程 / 学习笔记之k-nearest neighbors algorithm (k-NN)

学习笔记之k-nearest neighbors algorithm (k-NN)

内容导读

互联网集市收集整理的这篇技术教程文章主要介绍了学习笔记之k-nearest neighbors algorithm (k-NN)，小编现在分享给大家，供广大互联网技能从业者学习和参考。文章包含1125字，纯文字阅读大概需要2分钟。

内容图文

k-nearest neighbors algorithm - Wikipedia

  • https://en.wikipedia.org/wiki/K-nearest_neighbors_algorithm
  • Not to be confused with k-means clustering.
  • In pattern recognition, the k-nearest neighbors algorithm (k-NN) is a non-parametric method used for classification and regression.[1] In both cases, the input consists of the k closest training examples in the feature space. The output depends on whether k-NN is used for classification or regression.
  • k-NN is a type of instance-based learning, or lazy learning, where the function is only approximated locally and all computation is deferred until classification. The k-NN algorithm is among the simplest of all machine learning algorithms.

学习笔记之scikit-learn - 浩然119 - 博客园

  • https://www.cnblogs.com/pegasus923/p/9997485.html

Machine Learning with Python: k-Nearest Neighbor Classifier in Python

  • https://www.python-course.eu/k_nearest_neighbor_classifier.php

Refining a k-Nearest-Neighbor classification

  • https://www3.nd.edu/~steve/computing_with_data/17_Refining_kNN/refining_knn.html

原文：https://www.cnblogs.com/pegasus923/p/10417872.html

内容总结

以上是互联网集市为您收集整理的学习笔记之k-nearest neighbors algorithm (k-NN)全部内容，希望文章能够帮你解决学习笔记之k-nearest neighbors algorithm (k-NN)所遇到的程序开发问题。 如果觉得互联网集市技术教程内容还不错，欢迎将互联网集市网站推荐给程序员好友。

内容备注

版权声明：本文内容由互联网用户自发贡献，该文观点与技术仅代表作者本人。本站仅提供信息存储空间服务，不拥有所有权，不承担相关法律责任。如发现本站有涉嫌侵权/违法违规的内容， 请发送邮件至 gblab@vip.qq.com 举报，一经查实，本站将立刻删除。

内容手机端

扫描二维码推送至手机访问。

本文链接：https://qyyshop.com/info/1241346.html

来源：【匿名】