February 29, 2020 Journal article Open Access

M. Alagurajan; C. Vijayakumaran

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  <dc:contributor>Blue Eyes Intelligence Engineering  &amp; Sciences Publication(BEIESP)</dc:contributor>
  <dc:creator>M. Alagurajan</dc:creator>
  <dc:creator>C. Vijayakumaran</dc:creator>
  <dc:date>2020-02-29</dc:date>
  <dc:description>Machine learning Has performed a essential position within the estimation of crop yield for both farmers and consumers of the products. Machine learning techniques learn from data set related to the environment on which the estimations and estimation are to be made and the outcome of the learning process are used by farmers for corrective measures for yield optimization. This paper we explore various ML techniques utilized in crop yield estimation and provide the detailed analysis of accuracy of the techniques.</dc:description>
  <dc:identifier>https://zenodo.org/record/5593844</dc:identifier>
  <dc:identifier>10.35940/ijeat.C5775.029320</dc:identifier>
  <dc:identifier>oai:zenodo.org:5593844</dc:identifier>
  <dc:language>eng</dc:language>
  <dc:relation>issn:2249-8958</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:source>International Journal of Engineering and Advanced Technology (IJEAT) 9(3) 3506-3508</dc:source>
  <dc:subject>Machine Learning, Crop Yield,</dc:subject>
  <dc:subject>ISSN</dc:subject>
  <dc:subject>Retrieval Number</dc:subject>
  <dc:title>ML Methods for Crop Yield Prediction and  Estimation: An Exploration</dc:title>
  <dc:type>info:eu-repo/semantics/article</dc:type>
  <dc:type>publication-article</dc:type>
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