Module modularization method for fast achieving data mining analysis

Abstract

The invention relates to the technical field of data analysis processing, and particularly provides a module modularization method for fast achieving data mining analysis. According to the method, analysis is conducted on a functional process of an analysis procedure in which tool type data is mined and analyzed by using programming type data, a common method which is extracted from a data input procedure, an algorithmic procedure of data mining analysis and a analysis procedure of a data analysis result by data mining analysis is summarized, respective achievement is conducted through the module modularization method, assembly is conducted according to modularization, module modularization is thus conducted on different data input, analysis algorithms and analysis results, so that a process of a data mining analysis procedure is simplified, a method of fast achievement is provided for a user to conduct an application of a data mining analysis method, therefore, difficulty of the data mining analysis procedure is reduced, and a convenient and fast method is provided for the user when the user uses data analysis to conduct data mining.

Description

technical field [0001] The invention relates to the technical field of data analysis and processing, and in particular provides a modularized method for quickly realizing data mining and analysis. Background technique [0002] Entering the information age With the development of big data, more and more industries need data mining and analysis. The amount of data stored in computer files and databases is increasing at an exponential rate. At the same time, people expect to get more useful information from the data. information. However, the amount of data is getting larger and larger, and a new technology is needed to automatically and efficiently extract useful knowledge from massive data, and data mining technology was born from this. [0003] The application of data mining analysis needs to find out the business logic relationship of data in a large amount of data. With the development of data mining analysis tools, it can be realized through related software tools, such ...

AI Technical Summary

Problems solved by technology

[0003] The application of data mining analysis needs to find out the business logic relationship of data in a large amount of data. With the development of data mining analysis tools, it can be realized through related software tools, such as Carlementine, R language, Spark MLlib, etc., but these All tools require a certain degree of programming language implementation, which increases the difficulty of data mining analysis.

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