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  • 标题:Regression Problem Using Nerul Network to Predict Real-Value Output
  • 本地全文:下载
  • 作者:Rishabh Sharma ; Sudhanshu Sharma
  • 期刊名称:International Journal of Innovative Research in Science, Engineering and Technology
  • 印刷版ISSN:2347-6710
  • 电子版ISSN:2319-8753
  • 出版年度:2017
  • 卷号:6
  • 期号:3
  • 页码:3512
  • DOI:10.15680/IJIRSET.2017.0603092
  • 出版社:S&S Publications
  • 摘要:the essence of artificial intelligence is Machine learning. From past experiences Machine Learninglearns to make better thesmart programs performances. Machine learning system constructs the learning model whicheffectively “learns” how to predict from training data of given example. IT denotes a group of topics which mainlydeals with the formation and calculations of algorithms which make the pattern recognition, prediction andclassification, easy depend on the models which are derived from existing data. In this new period, to demonstrate thepromise of producing consistently accurate estimatesMachine learning is frequently in use. The keycontribution andpurposeof this review paper is to represent the overall analysis of the machine learning and provides machine-learningtechniques. This paper also studies the benefitsand drawbacksin different approachesof various machine learningalgorithms.
  • 关键词:unsupervised learning; machine learning; supervised learning
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