论文标题
高级KNN：一个成熟的机器学习系列
Advanced kNN: A Mature Machine Learning Series
论文作者
论文摘要
K-Nearest邻居（KNN）是机器学习和数据挖掘中使用的最突出，最简单，最基本的算法之一。但是，KNN的预测能力有限，即，如果KNN不属于训练数据集中的任何预定义类，则无法正确预测任何实例。本文的目的是提出一种高级KNN（A-KNN）算法，该算法将能够将实例分类为未知的实例，此前验证了它不属于任何预定义类。在三个不同的数据集（即虹膜植物数据集，bupa肝脏障碍数据集和alpha beta检测数据集）上比较了KNN和A-KNN的性能。 A-KNN的结果明显准确地检测未知实例。
k-nearest neighbour (kNN) is one of the most prominent, simple and basic algorithm used in machine learning and data mining. However, kNN has limited prediction ability, i.e., kNN cannot predict any instance correctly if it does not belong to any of the predefined classes in the training data set. The purpose of this paper is to suggest an Advanced kNN (A-kNN) algorithm that will be able to classify an instance as unknown, after verifying that it does not belong to any of the predefined classes. Performance of kNN and A-kNN is compared on three different data sets namely iris plant data set, BUPA liver disorder data set, and Alpha Beta detection data set. Results of A-kNN are significantly accurate for detecting unknown instances.
