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文章基本信息

  • 标题:Study on Machine Learning Algorithms
  • 本地全文:下载
  • 作者:B.Sandhiya ; R.P.S.Manikandan ; G.Anitha
  • 期刊名称:International Journal of Computer Trends and Technology
  • 电子版ISSN:2231-2803
  • 出版年度:2018
  • 卷号:65
  • 期号:1
  • 页码:39-43
  • DOI:10.14445/22312803/IJCTT-V65P106
  • 出版社:Seventh Sense Research Group
  • 摘要:Machine learning is the field evolved from Artificial Intelligence, goal is to mimic intelligent abilities of human by machines. Here come this paper gives the clear idea about classification algorithm. Classification is a supervised learning where the computer programs learn from the data given to it and the classify the data based on the observation. Classification algorithms are KNN, Decision tree, Random Tree, Support vector machine, Logistic Regression. Classification can be performed on both structured and unstructured data. The goal of classification problem is to find the category to which the new data fall. Data will falls under classification only when the desired output is discrete. Two types of classification, namely Binary classification and Multi label classification.Some examples are speech recognition, handwriting recognition, bio metric identification, document classification etc. In this paper, a novel learning about various Classification algorithms with example and types of classification
  • 关键词:Classification; SVM; Binary classification; Multi label classification.
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