کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6864841 1439552 2018 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A simple plug-in bagging ensemble based on threshold-moving for classifying binary and multiclass imbalanced data
ترجمه فارسی عنوان
یک پشته بسته بندی ساده در گروه بر اساس حرکت آستانه برای طبقه بندی داده های نامتقارن باینری و چند ستاره
کلمات کلیدی
داده های نامتعادل طبقه بندی باینری، طبقه بندی چند طبقه، گروه های بسته بندی انتخاب مجدد کالیبراسیون پشتی،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی
Class imbalance presents a major hurdle in the application of classification methods. A commonly taken approach is to learn ensembles of classifiers using rebalanced data. Examples include bootstrap averaging (bagging) combined with either undersampling or oversampling of the minority class examples. However, rebalancing methods entail asymmetric changes to the examples of different classes, which in turn can introduce their own biases. Furthermore, these methods often require specifying the performance measure of interest a priori, i.e., before learning. An alternative is to employ the threshold moving technique, which applies a threshold to the continuous output of a model, offering the possibility to adapt to a performance measure a posteriori, i.e., a plug-in method. Surprisingly, little attention has been paid to this combination of a bagging ensemble and threshold-moving. In this paper, we study this combination and demonstrate its competitiveness. Contrary to the other resampling methods, we preserve the natural class distribution of the data resulting in well-calibrated posterior probabilities. Additionally, we extend the proposed method to handle multiclass data. We validated our method on binary and multiclass benchmark data sets by using both, decision trees and neural networks as base classifiers. We perform analyses that provide insights into the proposed method.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 275, 31 January 2018, Pages 330-340
نویسندگان
, , ,