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Data normalization for use in Artificial Neural Networks often requires extensive statistical analysis. This paper presents an initial investigation of a case study involving credit card fraud detection, where Cluster Analysis was applied to data normalization. Early results obtained from the use of Artificial Neural Networks and Cluster Analysis on fraud detection has shown that neuronal inputs can...
This paper presents a neural network (NN) approach for determining the best design combination of product form elements that match a given product value represented by eco-product value (EpV) attributes. Twenty-seven representative office chairs are derived from 100 collected as the experimental samples by using multidimensional scaling and cluster analysis. Moreover, a morphological analysis is applied...
In this paper we propose a novel approach to constructing a discriminant visual codebook in a simple and extremely fast way as a one-pass, that we call Resource-Allocating Codebook (RAC), inspired by the Resource Allocating Network (RAN) algorithms developed in the artificial neural networks literature. Unlike density preserving clustering, this approach retains data spread out more widely in the...
An artificial neural network has got greater importance in the field of data mining. Although it may have complex structure, long training time, and uneasily understandable representation of results, neural network has high accuracy and is preferable in data mining. This research paper is aimed to improve efficiency and to provide accurate results on the basis of same behaviour data. To achieve these...
The Kohonen self organizing map (SOM) is an excellent tool in exploratory phase of data mining. The SOM is a popular tool that maps a high-dimensional space onto a small number of dimensions by placing similar elements close together, forming clusters. When the number of SOM units is large, to facilitate quantitative analysis of the map and the data, similar units needs to be grouped i.e., clustered...
Taking the example of designing classifier in intrusion detection system, this paper studies on samples selection problem for classifier and proposes a method fitting for large data set. First, use cluster analysis and the information known of classification to select boundary samples of each class. Then cluster for each class of the remaining non-border samples and adopt the method based on sample...
As the better generalization ability of clusterer ensemble methods, they are widely applied to diverse domains. But now many challenges still exist. One of the drawbacks of the ensemble is, ignoring the valuable information contained in the process of training component clusterers. This paper explores a new ensemble method for cluster analysis based on dynamic cooperation, and this method adjusts...
Recently quite much attention was given to the investigation of Particle Swarm Optimization algorithm (PSO). It was proved that PSO algorithm has exhibited good performance across wide range application problems. This paper proposes the use of PSO algorithm for decision making model updating. The decision making model is used to generate one-step forward investment decisions for stock markets. The...
The article is devoted to investigation of the problem of input attribute space formation for solution of the task of financial time series prediction with application of artificial neural networks. The new approach to solve this task is offered which is based on cluster analyses application. Artificial neural network of Kokhonen is applied as an instrument of cluster analyses. Comparison of the proposed...
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