A Data Reduction Method for Decision Table

A decision table and data technology, applied in the field of data processing, can solve the problems of wasting time and calculation times, and achieve the effect of good repeatability, simple calculation and fast calculation speed

CN106599049BActive Publication Date: 2019-08-27CENT SOUTH UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Publication Date
2019-08-27

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Abstract

The invention provides a decision table data reduction method. The method comprises the following steps: step one, judging whether the last condition attribute in a decision table data set is a decision table core attribute, adding the data of the attribute in a reduction set R if the last condition attribute is the decision table core attribute, and executing the step 2; deleting the last line of condition attribute data if the last condition attribute is not the decision table core attribute, and re-executing the step one; and step two, placing the line data corresponding to the decision table core attribute in the first line, and outputting the reduction set R after determining that an end condition is met, or else returning to step one. The method provided by the invention has the advantage of simply and effectively performing reduction on the decision table data.
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Description

technical field

[0001] The present invention relates to the technical field of data processing, and more specifically, relates to a data reduction method of a decision table. Background technique

[0002] At present, with the rapid development of data acquisition and storage technology, the problem of data redundancy is becoming more and more serious. It not only wastes storage space greatly, but also significantly reduces the performance of data-based modeling and decision-making algorithms. Rough set theory is a theory that specifically reduces data and extracts effective information from data. The core of this theory lies in data reduction. By deleting unimportant and redundant data and attributes, a streamlined new data set containing complete information is obtained, providing high-quality data for data-based analysis, modeling, decision-making, etc. source data.

[0003] Traditional data reduction methods often adopt a heuristic reduction structure based on attribute...

Examples

Embodiment Construction

[0009] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0010] The present invention mainly deals with decision table data, expressed as S=a |a∈At},{I a |a∈At}>, where U is the set of all samples, At=C∪D, C={c 1 ,c 2 ,...,c n} is called condition attribute set, D={d} is called decision attribute set.

[0011] figure 1 , in a specific embodiment of the present invention, shows the overall flow of a method for reducing decision table data. Generally speaking, it includes: step 1, judge whether the last conditional attribute in the decision table data set is the core attribute of the decision table, if so, add the data of this attribute to the reduction set R, and perform step 2; otherwise, delete the last column of condition...