k近邻算法knn 的相关内容

文章 2024-04-03 来自：开发者社区

Machine Learning机器学习之K近邻算法（K-Nearest Neighbors，KNN）

前言背景介绍： K近邻算法最早由美国的科学家 Thomas Cover 和 Peter Hart 在 1967 年提出，并且在之后的几十年中得到了广泛的研究和应用。KNN 算法是一种基于实例的学习方法，它不像其他算法一样需要对数据进行假设或者参数拟合，而是直接利用已知的数据样本进行预测。思想： KNN 算法的思想是基于特征空间中的样本点之间的距离来进行分类。它...

文章 2023-01-12 来自：开发者社区

K近邻算法（KNN）（包含手写体识别、约会类型识别的代码）

K近邻：KNN-（k-nearest neighbor classification）是有监督学习、属于判别模型、支持多分类以及回归、非线性、有预测函数、无优化目标、无优化求解算法。（算法地图）对应每个训练数据xi有对应的标签yi--监督学习；优缺点：优点：精度高、对异常值不敏感、无...

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更新时间 2024-04-30 19:31:11

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Machine Learning机器学习之K近邻算法（K-Nearest Neighbors，KNN）

K近邻算法（KNN）（包含手写体识别、约会类型识别的代码）

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