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A Decision Tree-Based Attribute Weighting Method and Text Classification Method

A text classification and decision tree technology, which is applied in text database clustering/classification, unstructured text data retrieval, special data processing applications, etc., can solve high time complexity, inapplicability and other problems, and achieve low time complexity , good classification accuracy, and the effect of improving classification performance

Inactive Publication Date: 2018-05-22
CHINA UNIV OF GEOSCIENCES (WUHAN)
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Problems solved by technology

However, the heuristic search process of the CFS attribute weighting method has too high time complexity, and it is not suitable for text data with high dimensions or even more than ten thousand dimensions.

Method used

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  • A Decision Tree-Based Attribute Weighting Method and Text Classification Method
  • A Decision Tree-Based Attribute Weighting Method and Text Classification Method
  • A Decision Tree-Based Attribute Weighting Method and Text Classification Method

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Embodiment Construction

[0054] The present invention will be further described below in conjunction with embodiment.

[0055] The present invention provides a kind of attribute weighting method based on decision tree, comprises the following steps:

[0056] (1) For a known training document set D, any document d in the training document set D is represented as a word vector form d=1 ,w 2 ,...w m >, where w i is the i-th word in document d, and m is the number of words in document d;

[0057] Use the following formula to calculate the information gain rate of each attribute in the training document set D:

[0058]

[0059] Among them, GainRatio(D,w i ) for the word w i Divide the information gain rate of the training document set D, Gain(D,w i ) for the word w i Divide the information gain of the training document set D, SplitInfo(D,w i ) represents the training document set D about the word w i split information;

[0060] Gain(D,w i ) is calculated by the following formula:

[0061] ...

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Abstract

The invention provides an attribute weighting method based on a decision tree. The attribute weighting method comprises the following steps: firstly, constructing the decision tree by an information gain rate standard, and then, calculating a weight according to the minimum depth of each attribute in a test in the decision tree. The invention simultaneously provides a polynomial nave Bayesian text classification method of the attribute weighting method based on the decision tree, a complementary set nave Bayesian text classification method of the attribute weighting method based on the decision tree and a polynomial and complementary set combination nave Bayesian text classification method of the attribute weighting method based on the decision tree. The attribute weighting method improves the classification precision of the original nave Bayesian text classifier and simultaneously maintains the conciseness and the time complexity of the original nave Bayesian algorithm.

Description

technical field [0001] The invention relates to a decision tree-based attribute weighting method and a text classification method, belonging to the technical field of artificial intelligence data mining classification. Background technique [0002] Naive Bayesian text classifier is often used to deal with text classification problems because of its simplicity and efficiency, but its attribute independence assumption affects its classification performance to some extent while making it efficient. Given a document d, the document is represented as a word vector of the form <w 1 ,w 2 ,...,w m >, Multinomial Naive Bayes (MNB), Complementary Naive Bayes (CNB) and the combined model of both (OVA) classify document d using Equations 1, 2 and 3, respectively. [0003] [0004] [0005] [0006] The symbol C in the above formula is a set of class labels, is the complement of category c (that is, other categories except category c), m is the number of words, w i (...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30
CPCG06F16/35
Inventor 蒋良孝张伦干李超群
Owner CHINA UNIV OF GEOSCIENCES (WUHAN)
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