Countermand 发表于 2025-3-23 13:06:02

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冒失 发表于 2025-3-23 15:11:30

Matroska Feature-Selection Method for Microarray Dataset (Method 2),. The Method 1 offers a 95 % CI for the error rate and coefficient. We obtained two means of the error rates, M1 and M2, in the training and validation samples and proposed a simple model selection procedure to choose the best model with a minimum M2. We compared two statistical LDFs and six MP-base

新娘 发表于 2025-3-23 21:07:09

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infringe 发表于 2025-3-23 23:55:22

Book 2016d discriminate LSD theoretically (Problem 2). We solved the defect of the generalized inverse matrices (Problem 3)..For more than 10 years, many researchers have struggled to analyze the microarray dataset that is LSD (Problem 5). If we call the linearly separable model "Matroska," the dataset consi

Goblet-Cells 发表于 2025-3-24 06:02:10

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Ruptured-Disk 发表于 2025-3-24 06:41:56

New Theory of Discriminant Analysis After R. Fisher978-981-10-2164-0

消耗 发表于 2025-3-24 14:16:20

New Theory of Discriminant Analysis,ely solve these problems through five mathematical programming-based linear discriminant functions (MP-based LDFs). First, I develop an optimal linear discriminant function using integer programming (IP-OLDF) based on a minimum number of misclassifications (minimum NM (MNM)) criterion. We consider d

Intrepid 发表于 2025-3-24 16:51:31

,Iris Data and Fisher’s Assumption,s. Because Fisher evaluates Fisher’s LDF with these data, such data are very popular for the evaluation of discriminant functions. Therefore, we call these data, “Fisher’s Iris data.” Because we can easily separate setosa from virginica and vercicolor through a scatter plot, we usually discriminate

AGGER 发表于 2025-3-24 20:00:42

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船员 发表于 2025-3-25 01:11:53

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查看完整版本: Titlebook: New Theory of Discriminant Analysis After R. Fisher; Advanced Research by Shuichi Shinmura Book 2016 Springer Science+Business Media Singap