Application of Multivariate Adaptive Regression Splines (MARS) to the Preference Mapping of Cheese Sticks
| ISSN: |
1750-3841
|
|---|---|
| Source: |
Blackwell Publishing Journal Backfiles 1879-2005
|
| Topics: |
Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
Process Engineering, Biotechnology, Nutrition Technology
|
| Notes: |
: A novel modeling technique named MARS (Multivariate Adaptive Regression Splines) can automate variable selection as well as model selection. The main purpose of this study was to apply MARS to consumer preference mapping using consumer test data for cheese sticks. The results show that MARS was capable of modeling consumer's preference patterns for cheese sticks. One distinct advantage of MARS in preference mapping is that it has the ability to model hedonic-scale response variables (such as overall acceptance, acceptance of appearance, flavor, and texture) from “Just About Right” (JAR) predictor variables (such as color, size, saltiness, breading, and cheese texture). In addition, MARS can reveal the underlying relationship between the predictors and the response in a piecewise regression function. This study shows that MARS has potential uncovering underlying patterns hidden in complex data.
|
| Type of Medium: |
Electronic Resource
|
| URL: |
| _version_ | 1798290358141976576 |
|---|---|
| autor | Xiong, R. Meullenet, J. F. |
| book_url | http://dx.doi.org/10.1111/j.1365-2621.2004.tb06353.x |
| datenlieferant | nat_lic_papers |
| hauptsatz | hsatz_simple |
| identnr | NLZ24320566X |
| insertion_date | 2012-04-27 |
| issn | 1750-3841 |
| journal_name | Journal of food science |
| materialart | 1 |
| notes | : A novel modeling technique named MARS (Multivariate Adaptive Regression Splines) can automate variable selection as well as model selection. The main purpose of this study was to apply MARS to consumer preference mapping using consumer test data for cheese sticks. The results show that MARS was capable of modeling consumer's preference patterns for cheese sticks. One distinct advantage of MARS in preference mapping is that it has the ability to model hedonic-scale response variables (such as overall acceptance, acceptance of appearance, flavor, and texture) from “Just About Right” (JAR) predictor variables (such as color, size, saltiness, breading, and cheese texture). In addition, MARS can reveal the underlying relationship between the predictors and the response in a piecewise regression function. This study shows that MARS has potential uncovering underlying patterns hidden in complex data. |
| package_name | Blackwell Publishing |
| publikationsjahr_anzeige | 2004 |
| publikationsjahr_facette | 2004 |
| publikationsjahr_intervall | 7999:2000-2004 |
| publikationsjahr_sort | 2004 |
| publikationsort | Oxford, UK |
| publisher | Blackwell Publishing Ltd |
| reference | 69 (2004), S. 0 |
| search_space | articles |
| shingle_author_1 | Xiong, R. Meullenet, J. F. |
| shingle_author_2 | Xiong, R. Meullenet, J. F. |
| shingle_author_3 | Xiong, R. Meullenet, J. F. |
| shingle_author_4 | Xiong, R. Meullenet, J. F. |
| shingle_catch_all_1 | Xiong, R. Meullenet, J. F. Application of Multivariate Adaptive Regression Splines (MARS) to the Preference Mapping of Cheese Sticks Blackwell Publishing Ltd : A novel modeling technique named MARS (Multivariate Adaptive Regression Splines) can automate variable selection as well as model selection. The main purpose of this study was to apply MARS to consumer preference mapping using consumer test data for cheese sticks. The results show that MARS was capable of modeling consumer's preference patterns for cheese sticks. One distinct advantage of MARS in preference mapping is that it has the ability to model hedonic-scale response variables (such as overall acceptance, acceptance of appearance, flavor, and texture) from “Just About Right” (JAR) predictor variables (such as color, size, saltiness, breading, and cheese texture). In addition, MARS can reveal the underlying relationship between the predictors and the response in a piecewise regression function. This study shows that MARS has potential uncovering underlying patterns hidden in complex data. 1750-3841 17503841 |
| shingle_catch_all_2 | Xiong, R. Meullenet, J. F. Application of Multivariate Adaptive Regression Splines (MARS) to the Preference Mapping of Cheese Sticks Blackwell Publishing Ltd : A novel modeling technique named MARS (Multivariate Adaptive Regression Splines) can automate variable selection as well as model selection. The main purpose of this study was to apply MARS to consumer preference mapping using consumer test data for cheese sticks. The results show that MARS was capable of modeling consumer's preference patterns for cheese sticks. One distinct advantage of MARS in preference mapping is that it has the ability to model hedonic-scale response variables (such as overall acceptance, acceptance of appearance, flavor, and texture) from “Just About Right” (JAR) predictor variables (such as color, size, saltiness, breading, and cheese texture). In addition, MARS can reveal the underlying relationship between the predictors and the response in a piecewise regression function. This study shows that MARS has potential uncovering underlying patterns hidden in complex data. 1750-3841 17503841 |
| shingle_catch_all_3 | Xiong, R. Meullenet, J. F. Application of Multivariate Adaptive Regression Splines (MARS) to the Preference Mapping of Cheese Sticks Blackwell Publishing Ltd : A novel modeling technique named MARS (Multivariate Adaptive Regression Splines) can automate variable selection as well as model selection. The main purpose of this study was to apply MARS to consumer preference mapping using consumer test data for cheese sticks. The results show that MARS was capable of modeling consumer's preference patterns for cheese sticks. One distinct advantage of MARS in preference mapping is that it has the ability to model hedonic-scale response variables (such as overall acceptance, acceptance of appearance, flavor, and texture) from “Just About Right” (JAR) predictor variables (such as color, size, saltiness, breading, and cheese texture). In addition, MARS can reveal the underlying relationship between the predictors and the response in a piecewise regression function. This study shows that MARS has potential uncovering underlying patterns hidden in complex data. 1750-3841 17503841 |
| shingle_catch_all_4 | Xiong, R. Meullenet, J. F. Application of Multivariate Adaptive Regression Splines (MARS) to the Preference Mapping of Cheese Sticks Blackwell Publishing Ltd : A novel modeling technique named MARS (Multivariate Adaptive Regression Splines) can automate variable selection as well as model selection. The main purpose of this study was to apply MARS to consumer preference mapping using consumer test data for cheese sticks. The results show that MARS was capable of modeling consumer's preference patterns for cheese sticks. One distinct advantage of MARS in preference mapping is that it has the ability to model hedonic-scale response variables (such as overall acceptance, acceptance of appearance, flavor, and texture) from “Just About Right” (JAR) predictor variables (such as color, size, saltiness, breading, and cheese texture). In addition, MARS can reveal the underlying relationship between the predictors and the response in a piecewise regression function. This study shows that MARS has potential uncovering underlying patterns hidden in complex data. 1750-3841 17503841 |
| shingle_title_1 | Application of Multivariate Adaptive Regression Splines (MARS) to the Preference Mapping of Cheese Sticks |
| shingle_title_2 | Application of Multivariate Adaptive Regression Splines (MARS) to the Preference Mapping of Cheese Sticks |
| shingle_title_3 | Application of Multivariate Adaptive Regression Splines (MARS) to the Preference Mapping of Cheese Sticks |
| shingle_title_4 | Application of Multivariate Adaptive Regression Splines (MARS) to the Preference Mapping of Cheese Sticks |
| sigel_instance_filter | dkfz geomar wilbert ipn albert |
| source_archive | Blackwell Publishing Journal Backfiles 1879-2005 |
| timestamp | 2024-05-06T08:15:27.839Z |
| titel | Application of Multivariate Adaptive Regression Splines (MARS) to the Preference Mapping of Cheese Sticks |
| titel_suche | Application of Multivariate Adaptive Regression Splines (MARS) to the Preference Mapping of Cheese Sticks |
| topic | ZA-ZE ZM |
| uid | nat_lic_papers_NLZ24320566X |