Please use this identifier to cite or link to this item:
https://ah.lib.nccu.edu.tw/handle/140.119/18177
DC Field | Value | Language |
---|---|---|
dc.creator | 林妙香;張源俊 | zh_TW |
dc.creator | Lin,Miao-hsiang ;Huang ,Su-yun ;Chang,Yuan-chin | - |
dc.date | 2004-01 | en_US |
dc.date.accessioned | 2008-12-19T06:53:08Z | - |
dc.date.available | 2008-12-19T06:53:08Z | - |
dc.date.issued | 2008-12-19T06:53:08Z | - |
dc.identifier.uri | https://nccur.lib.nccu.edu.tw/handle/140.119/18177 | - |
dc.description.abstract | This article considers the problem of educational placement. Several discriminant techniques are applied to a data set from a survey project of science ability. A profile vector for each student consists of five science-educational indictors. The students are intended to be placed into three reference groups: advanced, regular, and remedial. Various discriminant techniques, including Fisher’s discriminant analysis and kernel-based nonparametric discriminant analysis, are compared. The evaluation work is based on the leaving-one-out misclassification score. Results from the five school data sets and 500 bootstrap samples reveal that the kernel-based nonparametric approach with bandwidth selected by cross validation performs reasonably well. The authors regard kernel-based nonparametric procedures as desirable competitors to Fisher’s discriminant rule for handling problems of educational placement. | - |
dc.format | application/ | en_US |
dc.language | en | en_US |
dc.language | en-US | en_US |
dc.language.iso | en_US | - |
dc.relation | Journal of Educational and Behavioral Statistics, 29, 219-241 | en_US |
dc.title | Kernel-based discriminant techniques for educational placement | en_US |
dc.type | article | en |
item.grantfulltext | open | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.openairetype | article | - |
item.cerifentitytype | Publications | - |
item.languageiso639-1 | en_US | - |
item.fulltext | With Fulltext | - |
Appears in Collections: | 期刊論文 |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
219-240.pdf | 198.89 kB | Adobe PDF2 | View/Open |
Google ScholarTM
Check
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.