Target feature selection method based on three-way decision

Abstract

The invention discloses a target feature selection method based on a three-way decision. A feature selection algorithm based on a three-way decision theory is used for solving the identification problem under a high-dimension small sample. Aiming at the limitation that only one threshold value in a typical filtering algorithm ReliefF is used as a feature accepting and rejecting condition and the defect that a packaging algorithm needs a large amount of execution time, three decisions are introduced, the filtering algorithm and the packaging algorithm are combined, one threshold value is expanded into two threshold values on the basis of the traditional ReliefF algorithm, and the features are split into a positive domain, a negative domain and a boundary domain according to the feature weights; and the features of the three domains are selected respectively, so that the error-tolerant rate of the algorithm is increased to a certain extent, and the recognition performance is greatly improved. According to the invention, the accuracy of the learning model is used as a selection standard, and the defect of other algorithms in recognition accuracy is overcome.

Description

technical field [0001] The invention belongs to the technical field of target recognition, and in particular relates to a target feature selection method. Background technique [0002] With the rapid development of information technology, various fields have ushered in the era of big data. Big data includes two aspects: one is the large number of samples in the data set; the other is that the data contains large dimensions. With the advent of the era of big data, data mining has ushered in a wave of research, and object recognition is a kind of data mining. At present, more and more research results have been produced for massive and complex images, texts and other data. However, there may not necessarily be a large number of labeled samples in practical applications, for example, remote sensing pictures in military fields such as aerospace. In the case of high-dimensional data, most of the existing traditional algorithms are suitable for a large number of labeled samples...

AI Technical Summary

Problems solved by technology

However, the existing classical rough set theory has defects in dealing with uncertain data and numerical data. As a theory based on rough sets, the three-way decision-making can solve the above problems well.

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