دانلود مقاله ISI انگلیسی شماره 156974
کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
156974 2018 34 صفحه PDF سفارش دهید 7843 کلمه
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
A class center based approach for missing value imputation
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Knowledge-Based Systems, Available online 21 March 2018

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چکیده انگلیسی

Missing value imputation (MVI) is the major solution method for dealing with incomplete dataset problems in which the missing attribute values are replaced from a chosen set of observed data using some statistical methods, such as mean/mode, machine learning, or support vector machine methods. Although machine learning MVI approaches may produce reasonably good imputation results, they usually require larger imputation times than statistical approaches. In this paper, a Class Center based Missing Value Imputation (CCMVI) approach is introduced for producing effective imputation results more efficiently. It is based on measuring the class center of each class and then the distances between it and the other observed data are used to define a threshold for the later imputation. The experimental results based on numerical, categorical, and mixed data types of datasets show that the proposed CCMVI approach outperforms the other MVI approaches for both numerical and mixed datasets. In addition, it requires much less imputation time than the machine learning MVI methods.

خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.