The First Discriminant Theory of Linearly Separable Data
From Exams and Medical Diagnoses with Misclassifications to 169 Microarrays for Cancer Gene Diagnosis
- Hardcover
347 pages
- Release Date
12 April 2024
Summary
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. Author developed RIP (Optimal-linear discriminant function finding the combinatorial optimal solution) as Theory1 in decades ago, that found the minimum misclassifications. RIP discriminated 63 (=2…
Book Details
| ISBN-13: | 9789819994199 |
|---|---|
| ISBN-10: | 9819994195 |
| Author: | Shuichi Shinmura |
| Publisher: | Springer Verlag, Singapore |
| Imprint: | Springer Verlag, Singapore |
| Format: | Hardcover |
| Number of Pages: | 347 |
| Edition: | 2024th |
| Release Date: | 12 April 2024 |
| Dimensions: | 235mm x 155mm |
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About The Author
Shuichi Shinmura
Shuichi Shinmura is Emeritus Professor in Seikei University, Tokyo. His publication includes “High-dimensional Microarray Data Analysis: Cancer Gene Diagnosis and Malignancy Indexes by Microarray” (Springer Nature 2019) and “New Theory of Discriminant Analysis After R. Fisher: Advanced Research by the Feature Selection Method for Microarray Data” (Springer 2017).
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