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Self-training learning system and method based on random forest for anti-addiction system

A technology of random forest and learning method, applied in the field of self-training learning system based on random forest, can solve the problem of less anti-addiction system and achieve the effect of strong universal applicability

Active Publication Date: 2022-05-03
XIAOVO TECH +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, there is still little research work on anti-addiction systems, and this field is still in the early stages of development.

Method used

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  • Self-training learning system and method based on random forest for anti-addiction system
  • Self-training learning system and method based on random forest for anti-addiction system
  • Self-training learning system and method based on random forest for anti-addiction system

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Embodiment Construction

[0040] Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation modes, and various modifications or changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, in the case of no conflict, the following embodiments and features in the embodiments can be combined with each other.

[0041] see Figure 1 to Figure 5 . It should be noted that the structures, proportions, sizes, etc. shown in the drawings attached to this specification are only used to match the content disclosed in the specification, for those who are familiar with this technology to understand and read, a...

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Abstract

The present invention provides a random forest-based self-training learning system and method for an anti-addiction system. The method includes: performing PCA training on at least one marked game feature sequence to obtain a game feature sequence training set; The classifier identifies the unmarked game feature sequence, and adds the unmarked game feature sequence with the highest confidence to the game feature sequence training set; re-carries out PCA training to the data in the game feature sequence training set until reaching The preset number of cycles or the game feature sequence training set is no longer increased; the game feature sequence training set is used to identify the input test game feature sequence. The random forest-based self-learning method provided by the present invention is used to solve the problem that a large amount of game sequence data is unmarked in the anti-addiction system, and a better classification is constructed by using a large amount of unmarked game sequence data and a small amount of marked game sequence data device.

Description

technical field [0001] The invention relates to the technical field of machine learning, in particular to a random forest-based self-training learning system and method for an anti-addiction system. Background technique [0002] The significance of the game anti-addiction system is well known: it is designed to solve the current situation of minors addicted to online games, so that minors cannot rely on long-term online to obtain the growth of personal abilities and rewards in the game, and effectively control minors. The online time of individual users, and change the bad game habits that are not conducive to the physical and mental health of minors. [0003] From this point of view, the research and development of the anti-addiction system is imminent. At present, there is still little research work on anti-addiction systems, and this field is still in its early stages of development. Contents of the invention [0004] In order to solve the above-mentioned and other po...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G06N20/00
CPCG06F18/285G06F18/2135G06F18/214
Inventor 骆源徐彬方品应臣浩
Owner XIAOVO TECH