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{ "item_title" : "Support Vector Machines and Their Application in Chemistry and Biotechnology", "item_author" : [" Yizeng Liang", "Qing-Song Xu", "Hong-Dong Li "], "item_description" : "Presenting a clear bridge between theory and application, this volume provides a thorough description of the mechanism of support vector machines (SVMs) from the point of view of chemists and biologists. Topics discussed include elements and algorithms of support vector classification (SVC) machines and support vector regression machines (SVR), the kernel function for solving nonlinear problems, ensemble learning of SVMs, applications of SVMs to near-infrared data, SVMs and quantitative structure-activity/property relationships (QSAR/QSPR), quality control of traditional Chinese medicine by means of the chromatography fingerprint technique, and the use of SVMS in exploring the biological data produced in OMICS study. ", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/1/13/838/197/1138381977_b.jpg", "price_data" : { "retail_price" : "91.99", "online_price" : "91.99", "our_price" : "91.99", "club_price" : "91.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Support Vector Machines and Their Application in Chemistry and Biotechnology|Yizeng Liang

Support Vector Machines and Their Application in Chemistry and Biotechnology

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Overview

Presenting a clear bridge between theory and application, this volume provides a thorough description of the mechanism of support vector machines (SVMs) from the point of view of chemists and biologists. Topics discussed include elements and algorithms of support vector classification (SVC) machines and support vector regression machines (SVR), the kernel function for solving nonlinear problems, ensemble learning of SVMs, applications of SVMs to near-infrared data, SVMs and quantitative structure-activity/property relationships (QSAR/QSPR), quality control of traditional Chinese medicine by means of the chromatography fingerprint technique, and the use of SVMS in exploring the biological data produced in OMICS study.

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Details

  • ISBN-13: 9781138381971
  • ISBN-10: 1138381977
  • Publisher: CRC Press
  • Publish Date: September 2018
  • Dimensions: 9.21 x 6.14 x 0.45 inches
  • Shipping Weight: 0.67 pounds
  • Page Count: 211

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