An analytical method for determining informative sets of features (INP) is developed, taking into account the resource for criteria based on the use of a measure of dispersion of classified objects. The areas of existence of the solution are defined. The statements and properties for the Fischer-type information criterion are proved, using which the proposed analytical method for determining the INP guarantees optimal results in the sense of maximizing the selected functional. The appropriateness of choosing this type of informative criterion is justified. A method for transforming attributes is proposed. The universality of the method in relation to the type of features is shown. An algorithm for implementing this method is given. In addition, the paper discusses the dynamics of the growth of information volume in the world, problems related to big data, as well as problems and tasks of pre-processing data. The relevance of reducing the dimension of the feature space for performing data processing and visualization without unnecessary difficulties is proved. The disadvantages of existing methods and algorithms for selecting an informative set of features are shown.
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Akbaraliev, Bakhtiyorjon Bakirovich
"AN EFFECTIVE METHOD FOR ATTRIBUTE SUBSET SELECTION, CONSIDERING THE RESOURCE IN PATTERN RECOGNITION,"
Chemical Technology, Control and Management: Vol. 2020
, Article 9.
Available at: https://uzjournals.edu.uz/ijctcm/vol2020/iss4/9