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As a novel learning algorithm for single-hidden-layer feedforward neural networks, extreme learning machines (ELMs) have been a promising tool for regression and classification applications. However, it is not trivial for ELMs to find the proper number of hidden neurons due to the nonoptimal input weights and hidden biases. In this paper, a new model(More)
—Some disadvantages should be discussed deeply for the current reduction algorithms. To eliminate these limitations of classical algorithms based on positive region and conditional information entropy, a new conditional entropy, which could reflect the change of decision ability objectively, was defined with separating consistent objects form inconsistent(More)
To compose some happy melodies which have hierarchical structures, this paper proposes an automatic melody composition algorithm based on relations. First, various types of melody structure are formalized and saved into a database, so the melody structure form preferred by a user can be elected by human-computer interaction. Second, some sequences of(More)
—Recently, Extreme Learning Machine(ELM) has been a promising tool in solving a large range of regression applications. However, to our best knowledge, there are very few researches applying ELM to estimate mixture regression model. To improve the estimation performance, this paper extends the classical ELM to the scenario of mixture regression. First,(More)
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