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The First Discriminant Theory of Linearly Separable Data From Exams and Medical Diagnoses with Misclassifications to 169 Microarrays for Cancer Gene Diagnosis

This book deals with the first discriminant theory of linearly separable data (LSD), Theory3, based on the four ordinary LSD of Theory1 and 169 microarrays (LSD) of Theory2. Furthermore, you can quickly analyze the medical data with the misclassified patients which is the true purpose of diagnoses....

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Bibliographic Details
Main Author: Shinmura, Shuichi
Format: eBook
Language:English
Published: Singapore Springer Nature Singapore 2024, 2024
Edition:1st ed. 2024
Subjects:
Data Analysis And Big Data
Statistical Theory And Methods
Cancer Genetics And Genomics
Statistics 
Biostatistics
Discrete Optimization
Quantitative Research
Diagnosis
Cancer / Genetic Aspects
Mathematical Optimization
Biometry
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of Contents:
  • The most important knowledge by 27 Revolutionary Findings and the Outlook of this book
  • LINGO Programs Usage and New Facts by Iris Data
  • Swiss banknote data and CPD data
  • Test Pass/Fail Judgment and Japanese Compact Cars and Regular Cars
  • First Theory of Cancer Gene Data Analysis by 169 Microarrays: Four Universal Data Structures of Discriminant Data
  • Three Important Studies for Cancer Gene Diagnosis
  • Two-Step Practical Screening Method for Cancer Gene Diagnoses: Multivariate Oncogenes among 169 Microarrays

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