کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
402595 676968 2015 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Feature selection with redundancy-complementariness dispersion
ترجمه فارسی عنوان
انتخاب ویژگی با پراکندگی مکمل انعقاد
کلمات کلیدی
طبقه بندی، انتخاب ویژگی، ارتباط، افزونگی، نزدیک بینی پراکندگی مکمل انعقاد
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی


• We use inter-correlation of features to represent redundancy and complementariness.
• We add a modification item for feature complementariness in the evaluation function.
• Redundancy-complementariness dispersion is used to address the interference effect.

Feature selection has attracted significant attention in data mining and machine learning in the past decades. Many existing feature selection methods eliminate redundancy by measuring pairwise inter-correlation of features, whereas the complementariness of features and higher inter-correlation among more than two features are ignored. In this study, a modification item concerning feature complementariness is introduced in the evaluation criterion of features. Additionally, in order to identify the interference effect of already-selected False Positives (FPs), the redundancy-complementariness dispersion is also taken into account to adjust the measurement of pairwise inter-correlation of features. To illustrate the effectiveness of proposed method, classification experiments are applied with four frequently used classifiers on ten datasets. Classification results verify the superiority of proposed method compared with seven representative feature selection methods.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Knowledge-Based Systems - Volume 89, November 2015, Pages 203–217
نویسندگان
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