A Text Classification Method Based on Improved KNN

Abstract

The invention provides an improvement-based KNN (K Nearest Neighbor) text classification method. The method comprises the following steps: preprocessing a training text, computing the feature vector of each training sample, and constructing a feature vector spatial model of a training set; defining a density and a distance, defining a density and a distance, defining a whole sample space into a plurality of spherical regions and outliers according to types, and storing as a training set library; during testing, judging whether a text to be tested falls into a certain spherical region, judging the type of the text to be tested according to a corresponding mark number, otherwise, using the outliers and the center point of each sphere as a training set library, calling a KNN algorithm, and judging the type of the text to be tested. By adopting the method provided by the invention, the classification speed, classification accuracy and data skew sensitivity are considered. The method can be well applied to the classification problem of non-spherical distribution, and is particularly suitable for a text classification problem having a high-dimension feature vector and a distribution irregularity feature.

Description

technical field [0001] The invention belongs to the technical field of verification and confirmation of nuclear safety level software, and in particular relates to an improved KNN-based text classification method. Background technique [0002] In recent years, with the gradual standardization of the software development process, the quality requirements for technical documents are getting higher and higher, especially in the process of software development for nuclear safety level, a large number of technical documents, such as requirements documents, design documents, etc., are generated. According to the requirements of relevant nuclear power standards, each requirement item and design item must meet the requirements of certain evaluation rules; and with the iterative development of the software, the technical documents are constantly updated and upgraded, aiming at each version of the document Each item (such as a requirement item or a design item) must also meet the requ...

AI Technical Summary

Problems solved by technology

[0004] Aiming at the problem that the accuracy and speed cannot be taken into account in the existing text classification algorithm, the present invention proposes an improved text classification algorithm based on the KNN algorithm, and uses text classification technology to solve the rule matching and failure mode matching problems in software reliability evaluation and analysis

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