کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
536110 870459 2010 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Semi-supervised geodesic Generative Topographic Mapping
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Semi-supervised geodesic Generative Topographic Mapping
چکیده انگلیسی

We present a novel semi-supervised model, SS-Geo-GTM, which stems from a geodesic distance-based extension of Generative Topographic Mapping that prioritizes neighbourhood relationships along a generated manifold embedded in the observed data space. With this, it improves the trustworthiness and the continuity of the low-dimensional representations it provides, while behaving robustly in the presence of noise. In SS-Geo-GTM, the model prototypes are linked by the nearest neighbour to the data manifold constructed by Geo-GTM. The resulting proximity graph is used as the basis for a class label propagation algorithm. The performance of SS-Geo-GTM is experimentally assessed, comparing positively with that of an Euclidean distance-based counterpart and with those of alternative manifold learning methods.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition Letters - Volume 31, Issue 3, 1 February 2010, Pages 202–209
نویسندگان
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