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An approach to clustering feature tree transformation into feature vectors


P.V. Dudarin – Post-graduate Student, Ulyanovsk State Technical University
N.G. Yarushkina – Dr.Sc.(Eng.), Professor, Head of Department «Information Systems», Ulyanovsk State Technical University

Almost any machine learning algorithm includes a feature selection and feature extraction phase. In case of non-vector features a transformation into feature vectors is needed. Feature extraction algorithm determines the volume and quality of information enclosed in features and quality of clustering. Thus this kind of transformation is important part of clustering procedure. In this paper an approach to clustering feature tree transformation into feature vectors is proposed. Presented approach allows saving hierarchy information and reducing feature space dimension. An efficiency of transformation is shown in the experiment part with different clustering algorithms. There is a result analysis at the end of the paper.

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