Applying Machine Learning For Automated Classification Of Biomedical Data In Sub

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Applying Machine Learning For Automated Classification Of Biomedical Data In Sub

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Applying Machine Learning For Automated Classification Of Biomedical Data In Sub

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Applying Machine Learning For Automated Classification Of Biomedical Data In Sub

This Book Describes Efforts To Improve Subject-independent Automated Classification Techniques Using A Better Feature Extraction Method And A More Efficient Model Of Classification. It Evaluates Three Popular Saliency Criteria For Feature Selection, Showing That They Share Common Limitations, Including Time-consuming And Subjective Manual De-facto Standard Practice, And That Existing Automated Efforts Have Been Predominantly For Subject Dependent Setting. It Then Proposes A Novel Approach For Anomaly Detection, Demonstrating Its Effectiveness And Accuracy For Automated Classification Of Biomedical Data, And Arguing Its Applicability To A Wider Range Of Unsupervised Machine Learning Applications In Subject-independent Settings.
  • Brand: Springer Nature B.V
  • Category: Computing & Internet
  • Format: Paperback
  • Language: English
  • Publication Date: 2019-01-25
  • Publisher / Label: Springer Nature B.V
  • Author: Thuy T. Pham
  • Number of Pages: 124
  • Fruugo ID: 557181831-1125451089
  • ISBN: 9783030075187
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