Machine learning algorithm resource sharing method and system based on unified description expression

A machine learning and resource sharing technology, applied in machine learning, based on specific mathematical models, instruments, etc., can solve problems such as high difficulty of machine learning algorithms

Pending Publication Date: 2020-10-23
WUHAN UNIV
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

[0005] The technical problem solved by the present invention is to provide a machine learning algorithm resource sharing method and system based on un

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  • Machine learning algorithm resource sharing method and system based on unified description expression
  • Machine learning algorithm resource sharing method and system based on unified description expression
  • Machine learning algorithm resource sharing method and system based on unified description expression

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Embodiment Construction

[0041] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. The following examples are used to illustrate the present invention and are not intended to limit the scope of the present invention.

[0042] Such as figure 1 As shown, the method for sharing machine learning algorithm resources based on unified description and expression in the embodiment of the present invention includes the following steps:

[0043] Step 1. Unified description and expression of machine learning algorithms: sort out and summarize the feature items that affect the selection of machine learning algorithm resources, build a six-tuple unified description model for machine learning algorithms, and use XML language for formal expression to form inf...

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Abstract

The invention discloses a machine learning algorithm resource sharing method and system based on unified description expression. The method comprises the steps: building a six-tuple unified description model of a machine learning algorithm, and carrying out the formalized expression to form knowledge related to the description of the machine learning algorithm; designing a knowledge base structurebased on the knowledge related to the machine learning algorithm description, storing and organizing algorithm knowledge, and designing a corresponding database access interface to support algorithmknowledge base management; based on the requirements of a knowledge base and an upper-layer application for algorithms, a candidate machine learning algorithm set is obtained through a matching method, and then an optimal machine learning algorithm is determined through an evaluation method; and based on the optimal machine learning algorithm, executing a target machine learning algorithm, and converting input into output for further analysis and decision making of an upper-layer application. According to the method, the problem that an upper application selects an appropriate algorithm from massive machine learning algorithm resources can be solved, and algorithm resource sharing and intelligent matching can be realized.

Description

technical field [0001] The invention relates to the technical field of computer data processing, in particular to a method and system for sharing machine learning algorithm resources based on unified description and expression. Background technique [0002] Machine learning is a method driven by big data to solve data analysis and data mining problems. At this stage, information networks, sensor devices, and intelligent applications will generate a large amount of data. Traditional data processing methods based on a single model or method are difficult to gain insight into the information and knowledge contained in big data. It is necessary to introduce a variety of machine learning algorithms for exploratory analysis. . [0003] In the face of large-scale machine learning algorithm resources, it is difficult to select an algorithm that is suitable for analysis needs. Even experienced data scientists and computer algorithm developers have difficulty mastering so much machin...

Claims

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Application Information

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IPC IPC(8): G06F16/28G06N7/00G06N20/00
CPCG06F16/285G06F16/288G06N20/00G06N7/01
Inventor 向隆刚李雅丽
Owner WUHAN UNIV
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