Self-organizing maps with information theoretic learning
نویسندگان
چکیده
منابع مشابه
Self-organizing maps with information theoretic learning
The self organizing map (SOM) is one of the popular clustering and data visualization algorithms and has evolved as a useful tool in pattern recognition, data mining since it was first introduced by Kohonen. However, it is observed that the magnification factor for such mappings deviates from the information-theoretically optimal value of 1 (for the SOM it is 2/3). This can be attributed to the...
متن کاملGTSOM: Game Theoretic Self-organizing Maps
Self-Organizing Maps (SOM) is a powerful tool for clustering and discovering patterns in data. Input vectors are compared to neuron weight vectors to form the SOM structure. An update of a neuron only benefits part of the feature map, which can be thought of as a local optimization problem. A global optimization model could improve representation to data by a SOM. Game Theory is adopted to anal...
متن کاملInformation Visualization with Self-Organizing Maps
The Self-Organizing Map (SOM) is an unsupervised neural network algorithm that projects highdimensional data onto a two-dimensional map. The projection preserves the topology of the data so that similar data items will be mapped to nearby locations on the map. Despite the popular use of the algorithm for clustering and information visualisation, a system has been lacking that combines the fast ...
متن کاملRapid learning with parametrized self-organizing maps
The construction of computer vision and robot control algorithms from training data is a challenging application for artiicial neural networks. However, many practical applications require an approach that is workable with a small number of data examples. In this contribution, we describe results on the use of \Parametrized Self-organizing Maps" (\PSOMs") with this goal in mind. We report resul...
متن کاملusing game theory techniques in self-organizing maps training
شبکه خود سازمانده پرکاربردترین شبکه عصبی برای انجام خوشه بندی و کوانتیزه نمودن برداری است. از زمان معرفی این شبکه تاکنون، از این روش در مسائل مختلف در حوزه های گوناگون استفاده و توسعه ها و بهبودهای متعددی برای آن ارائه شده است. شبکه خودسازمانده از تعدادی سلول برای تخمین تابع توزیع الگوهای ورودی در فضای چندبعدی استفاده می کند. احتمال وجود سلول مرده مشکلی اساسی در الگوریتم شبکه خودسازمانده به حسا...
ذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Neurocomputing
سال: 2015
ISSN: 0925-2312
DOI: 10.1016/j.neucom.2013.12.059