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Data transformation method is well known in Knowledge Discovery in Databases (KDD) process and data mining in order to transform raw data into concepts at higher levels concepts. A number of promising data transformation methods have been studied and developed. Despite the great advantages offered by these data transformation methods, these methods still requires further improvement. In order to handle...
A new method for design of a classification system using the feature extraction and evolutionary programming (EP) are discussed. In this paper, a neuro-fuzzy classification model (NFCM) is proposed. The optimal fuzzy membership functions of the NFCM are extracted from the training data using EP. The NFCM contains the feature extraction unit and the inference unit. In order to improve the proposed...
This paper introduces the cosine neural network (COSNN) and shows how it can be used to process data with missing components without imputation. It uses a cosine basis function with a weighted norm which can be trained to match the input data, or it can be set to zero to 'ignore' missing data components. The COSNN is compared to feedforward neural networks using deletion and imputation. The COSNN...
The imbalanced data sets are often encountered in business, industry and real life applications. In this paper, the novel fitness function in genetic algorithms to optimize neural networks is proposed for solving the classification problems in imbalanced data sets. Not only the parameters of neural networks but also the links-pruning between neurons are regarded as an optimization problem in this...
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