Determination of the consensus partition and cluster analysis of subjects in a free sorting task experiment
•We advocate using Adjusted Rand index as a measure of similarity between partitions given by subjects in a free sorting task.•A technique for determining a consensus partition is proposed.•The problem of segmenting subjects is tackled and a strategy based on Adjusted Rand index is described.•The cl...
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Published in | Food quality and preference Vol. 32; pp. 107 - 112 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
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Elsevier Ltd
01.03.2014
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Abstract | •We advocate using Adjusted Rand index as a measure of similarity between partitions given by subjects in a free sorting task.•A technique for determining a consensus partition is proposed.•The problem of segmenting subjects is tackled and a strategy based on Adjusted Rand index is described.•The clustering technique is applied to the free sorting of wine aromas by a panel of subjects.
The purpose of this study is to investigate the problem of clustering subjects in a free sorting task. We compare different measures of agreement between partitions. From a simulation study, we advocate using the Adjusted Rand index. On the basis of this index, we propose a technique for determining a consensus partition as a summary of the initial partitions given by the subjects after a categorization task. Thereafter, the problem of clustering the subjects is explored. For this purpose, a method combining hierarchical clustering and a partitioning algorithm is described. These techniques are applied to a case study of the perception of wine aromas by a panel of subjects. |
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AbstractList | The purpose of this study is to investigate the problem of clustering subjects in a free sorting task. We compare different measures of agreement between partitions. From a simulation study, we advocate using the Adjusted Rand index. On the basis of this index, we propose a technique for determining a consensus partition as a summary of the initial partitions given by the subjects after a categorization task. Thereafter, the problem of clustering the subjects is explored. For this purpose, a method combining hierarchical clustering and a partitioning algorithm is described. These techniques are applied to a case study of the perception of wine aromas by a panel of subjects. The purpose of this study is to investigate the problem of clustering subjects in a free sorting task. We compare different measures of agreement between partitions. From a simulation study, we advocate using the Adjusted Rand index. On the basis of this index, we propose a technique for determining a con. sensus partition as a summary of the initial partitions given by the subjects after a categorization task. Thereafter, the problem of clustering the subjects is explored. For this purpose, a method combining hierarchical clustering and a partitioning algorithm is described. These techniques are applied to a case study of the perception of wine aromas by a panel of subjects. (C) 2013 Elsevier Ltd. All rights reserved. •We advocate using Adjusted Rand index as a measure of similarity between partitions given by subjects in a free sorting task.•A technique for determining a consensus partition is proposed.•The problem of segmenting subjects is tackled and a strategy based on Adjusted Rand index is described.•The clustering technique is applied to the free sorting of wine aromas by a panel of subjects. The purpose of this study is to investigate the problem of clustering subjects in a free sorting task. We compare different measures of agreement between partitions. From a simulation study, we advocate using the Adjusted Rand index. On the basis of this index, we propose a technique for determining a consensus partition as a summary of the initial partitions given by the subjects after a categorization task. Thereafter, the problem of clustering the subjects is explored. For this purpose, a method combining hierarchical clustering and a partitioning algorithm is described. These techniques are applied to a case study of the perception of wine aromas by a panel of subjects. |
Author | Courcoux, Ph Qannari, E.M. Faye, P. |
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Cites_doi | 10.1080/01621459.1971.10482356 10.1007/s11634-011-0087-6 10.1016/j.foodqual.2003.09.002 10.1016/j.foodqual.2006.03.020 10.1016/j.foodqual.2009.01.003 10.1016/j.foodqual.2003.10.005 10.1016/j.foodqual.2009.02.010 10.1016/j.foodqual.2004.04.009 10.1016/j.foodqual.2008.05.001 10.1007/s00357-006-0017-z 10.1007/s003579900043 10.1016/j.foodqual.2006.07.006 10.1016/0950-3293(95)98553-U 10.1007/BF01908075 10.1016/j.foodqual.2006.09.003 10.1007/s003579900034 10.1016/j.foodqual.2007.08.001 |
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Keywords | Partitions Consensus partition Clustering Rand index Free sorting Adjusted Rand index |
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SubjectTerms | Adjusted Rand index algorithms case studies Chemical and Process Engineering cluster analysis Clustering Consensus partition Engineering Sciences Food engineering Free sorting Life Sciences odors Partitions Rand index wines |
Title | Determination of the consensus partition and cluster analysis of subjects in a free sorting task experiment |
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