Multi-level progressive classification method and system based on neural network and Bayesian model

Abstract

The invention provides a multi-level progressive classification method and system based on a neural network and a Bayesian model, and the method comprises the steps: carrying out the data preprocessing of the neural network, and preparing a feature vector and a prediction result of a neural network training model for a first model; training a neural network: training a neural network model on theprepared data, and constructing a large-class hierarchical classifier model; training a Bayesian model, and establishing a Bayesian network model of the category under each large category; and predicting the samples to be classified. According to the method, advantages and disadvantages of different models are fully utilized, batch training is carried out on mass data according to requirements oflevels, labels of samples to be classified are determined through a series of models, and corresponding solutions are provided for training and prediction of multiple models.

Description

technical field [0001] The invention belongs to the field of data mining and modeling, and in particular relates to a multi-level progressive classification method and system under multi-label multi-level classification based on neural network and Bayesian model. Background technique [0002] Automatic text classification technology refers to the technology of automatically classifying texts under a predefined classification system through the data processing capabilities of computers. This technique associates one or more categories based on the characteristics of the given data. Thereby realizing multi-label classification of text. [0003] Multi-label categories of massive data are very common in daily life. For example, in the field of patents, as of June 2018, the number of invention patents published in my country has exceeded 8 million. In order to quickly and conveniently retrieve relevant documents, document classification is particularly important. Patents are d...

AI Technical Summary

Problems solved by technology

[0006] In order to solve the problem that the multi-label classification of massive data is difficult to train, the present invention proposes a hierarchical multi-label classification method, which makes full use of the advantages and disadvantages of different models, and performs batch training on massive data according to the needs of the hierarchy, thus a series of The model determines the label of the sample to be classified, and proposes a corresponding solution for the training and prediction of multiple models

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