文章基本信息

标题：An Efficient K Nearest Neighbor Imputation Method For Missing Values
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作者：M.Gobi ; G.Buvaanyaa
期刊名称：International Journal of Advances in Engineering and Management
电子版ISSN：2395-5252
出版年度：2020
卷号：2
期号：2
页码：11-15
语种：English
出版社：IJAEM JOURNAL
摘要：Classification is a data mining technique used to predict group membership for data instances within a given dataset. It is used for classifying data into different classes by considering some constrains. Classification is considered as an example of supervised learning as training data associated with class labels is given as input. Predictive classification as a wide range of application in data mining. Most real data set have missing values which affects the accuracy of classifiers. This paper will investigate predictive performance of missing data using KNN classifier.
关键词：Classification;Data Mining;Classification Technique;K- NN classifier;Predictive