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The general classification is a machine learning task that tries to assign the best class to a given unknown input vector based on past observations (training data). Most of developed algorithms are very time consuming for large datasets (Support Vector Machine, Deep Neural Networks, etc.). Extreme Learning Machine (ELM) is a high quality classification algorithm that gains much popularity in recent...
Linguistic word nets usually focus on the semantic content and content relations of nouns while not taking into account to what degree those nouns can also reflect visual impressions in a user specific manner. Recently Color Design SNS like COLOURlovers or Adobe Color CC have gained popularity and the huge corpus of available data allows for gaining new insights into the way user associate color designs...
Multi-variable data relations can define a partial differential equation, which describes an unknown complex function on a basis of discrete observations, using the similarity model analysis methods. Time-series can form an ordinary differential equation, which is analogously possible to replace by partial derivatives of the same type time-dependent observations. Polynomial neural networks can compose...
BP neural network is an important and efficient method in machine learning. But there are some drawbacks lying in its local minimum and slow convergence speed. To solve these problems and enhance the performance of BP network, an optimized BP neural network by genetic algorithm is proposed in this paper. Firstly, we design a fitness function based on genetic algorithm for the view of obtaining the...
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