{"title":"建立基于先验对数正态分布的质谱分类诚实树","authors":"Cheng-Jian Xu, Ping He, Yizeng Liang","doi":"10.6339/JDS.2003.01(4).179","DOIUrl":null,"url":null,"abstract":"Structure elucidation is one of big tasks for analytical researcher and it often needs an efficient classifier. The decision tree is especially attractive for easy understanding and intuitive represen- tation. However, small change in the data set due to the experiment error can often result in a very different series of split. In this pa- per, a prior logarithm normal distribution is adopted to weight the original mass spectra. It helps to building an honest tree for later structure elucidation.","PeriodicalId":73699,"journal":{"name":"Journal of data science : JDS","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Building an Honest Tree for Mass Spectra Classification Based on Prior Logarithm Normal Distribution\",\"authors\":\"Cheng-Jian Xu, Ping He, Yizeng Liang\",\"doi\":\"10.6339/JDS.2003.01(4).179\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Structure elucidation is one of big tasks for analytical researcher and it often needs an efficient classifier. The decision tree is especially attractive for easy understanding and intuitive represen- tation. However, small change in the data set due to the experiment error can often result in a very different series of split. In this pa- per, a prior logarithm normal distribution is adopted to weight the original mass spectra. It helps to building an honest tree for later structure elucidation.\",\"PeriodicalId\":73699,\"journal\":{\"name\":\"Journal of data science : JDS\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of data science : JDS\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.6339/JDS.2003.01(4).179\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of data science : JDS","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.6339/JDS.2003.01(4).179","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Building an Honest Tree for Mass Spectra Classification Based on Prior Logarithm Normal Distribution
Structure elucidation is one of big tasks for analytical researcher and it often needs an efficient classifier. The decision tree is especially attractive for easy understanding and intuitive represen- tation. However, small change in the data set due to the experiment error can often result in a very different series of split. In this pa- per, a prior logarithm normal distribution is adopted to weight the original mass spectra. It helps to building an honest tree for later structure elucidation.