The book is currently out of stock
More about the book
The book uniquely compares eight linear discriminant functions (LDFs) across various datasets, including Fisher's iris data and medical data with collinearities. It introduces a 100-fold cross-validation method tailored for small samples and presents a straightforward model selection procedure to identify the optimal model based on minimum M2. The Revised IP-OLDF, evaluated using the MNM criterion, demonstrates superior performance compared to other M2s across the examined datasets, making it a significant contribution to statistical modeling and data analysis.
Book purchase
New Theory of Discriminant Analysis After R. Fisher, Shuichi Shinmura
- Language
- Released
- 2018
- product-detail.submit-box.info.binding
- (Paperback)
We’ll email you as soon as we track it down.
Payment methods
No one has rated yet.
- Language
- English
- Authors
- Shuichi Shinmura
- Publisher
- Springer
- Released
- 2018
- Format
- Paperback
- Pages
- 228
- ISBN10
- 9811095469
- ISBN13
- 9789811095467
- Series
- Description
- The book uniquely compares eight linear discriminant functions (LDFs) across various datasets, including Fisher's iris data and medical data with collinearities. It introduces a 100-fold cross-validation method tailored for small samples and presents a straightforward model selection procedure to identify the optimal model based on minimum M2. The Revised IP-OLDF, evaluated using the MNM criterion, demonstrates superior performance compared to other M2s across the examined datasets, making it a significant contribution to statistical modeling and data analysis.