{"title":"Research on Classification Method of Piano Teaching Resources Based on Multiple Logical Regression","authors":"Zhichao Yu","doi":"10.1109/ICVRIS.2019.00046","DOIUrl":null,"url":null,"abstract":"In order to solve the problem that the classification of piano teaching resources is not effective at present, a research on the classification method of piano teaching resources based on multiple logistic regression is proposed. Firstly, different characteristic categories in piano teaching resources are collected and extracted. Combined with multiple logistic regression classification algorithms, different characteristic factors in teaching materials are classified into categories and sequences, and finally the reasonable classification of piano teaching resources is realized. Finally, the experiment proves that the classification method of piano teaching resources based on multiple logistic regression is more practical and effective than the traditional classification method.","PeriodicalId":294342,"journal":{"name":"2019 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICVRIS.2019.00046","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In order to solve the problem that the classification of piano teaching resources is not effective at present, a research on the classification method of piano teaching resources based on multiple logistic regression is proposed. Firstly, different characteristic categories in piano teaching resources are collected and extracted. Combined with multiple logistic regression classification algorithms, different characteristic factors in teaching materials are classified into categories and sequences, and finally the reasonable classification of piano teaching resources is realized. Finally, the experiment proves that the classification method of piano teaching resources based on multiple logistic regression is more practical and effective than the traditional classification method.