{"title":"预测数据挖掘的基础","authors":"N. Jovanovic, V. Milutinovic, Z. Obradovic","doi":"10.1109/NEUREL.2002.1057967","DOIUrl":null,"url":null,"abstract":"The aim of this paper is to introduce a novel reader to the topic of predictive data mining (DM) by discussing technical aspects and requirements of common mining tools. A description of DM scope is followed by comparing DM to related data management and analysis techniques. This is followed by a discussion of a typical predictive DM process, and some of the more successful algorithms and software packages.","PeriodicalId":347066,"journal":{"name":"6th Seminar on Neural Network Applications in Electrical Engineering","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Foundations of predictive data mining\",\"authors\":\"N. Jovanovic, V. Milutinovic, Z. Obradovic\",\"doi\":\"10.1109/NEUREL.2002.1057967\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The aim of this paper is to introduce a novel reader to the topic of predictive data mining (DM) by discussing technical aspects and requirements of common mining tools. A description of DM scope is followed by comparing DM to related data management and analysis techniques. This is followed by a discussion of a typical predictive DM process, and some of the more successful algorithms and software packages.\",\"PeriodicalId\":347066,\"journal\":{\"name\":\"6th Seminar on Neural Network Applications in Electrical Engineering\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-12-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"6th Seminar on Neural Network Applications in Electrical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NEUREL.2002.1057967\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"6th Seminar on Neural Network Applications in Electrical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NEUREL.2002.1057967","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The aim of this paper is to introduce a novel reader to the topic of predictive data mining (DM) by discussing technical aspects and requirements of common mining tools. A description of DM scope is followed by comparing DM to related data management and analysis techniques. This is followed by a discussion of a typical predictive DM process, and some of the more successful algorithms and software packages.