کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
407015 678124 2014 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Incremental min–max projection analysis for classification
ترجمه فارسی عنوان
تجزیه و تحلیل مینا افزایشی برای طبقه بندی
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی

For data classification, the standard implementation of projection algorithms do not scale well with large dataset size. It makes the computation of large samples infeasible. In this paper, we utilize a block optimization strategy to propose a new locally discriminant projection algorithm termed min–max projection analysis (MMPA). The algorithm takes into account both intra-class and interclass geometries and also possesses the orthogonality property. Furthermore, an incremental MMPA is proposed to learn the local discriminant subspace with newly inserted data by employing the idea of singular value decomposition updating algorithm. Moreover, we extend MMPA to the semi-supervised case and nonlinear case, namely, semi-supervised MMPA and kernel MMPA. The experimental results on image database, hand written digit database, and face database demonstrate the effectiveness of those proposed algorithms.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 123, 10 January 2014, Pages 121–130
نویسندگان
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