Feature selection method based on word frequency reordering at document level
A feature selection method and reordering technology, applied in unstructured text data retrieval, text database clustering/classification, etc., can solve the problem of low classification accuracy, and achieve the effect of improving classification accuracy
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[0041] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.
[0042] Relevant definitions in the present invention are as follows:
[0043] Definition 1: word frequency, entry t i in document d j The ratio of the number of occurrences in this document to the total number of entries in this document, using tf ij express.
[0044] Definition 2: Intra-class term frequency sum, entry t i in a category C k The sum of the word frequencies of all documents in tf ki Indicates that the calculation formula is as follows:
[0045]
[0046] Among them, k is the category information label, N is the total number of documents in the data set, I(d j , C k ) is to judge the document d j Whether it belongs to category C k formula,
[0047] Definition 3: The total term frequency sum, the term t in each document in the entire data set i The sum of the word frequency, use tfi Indicates that the calculation ...
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