TY - JOUR
T1 - Fuzzy classification for farm household characterization
AU - Salasya, B.
AU - Stoorvogel, J.
N1 - http://www.scopus.com/inward/record.url?eid=2-s2.0-77953605045&partnerID=MN8TOARS
PY - 2010
Y1 - 2010
N2 - Most household classifications use hard classification procedures that limit a household to only one cluster. In this paper, fuzzy classification, in which individuals can belong totally, partially or not at all to a particular cluster, with membership showing how well they fit in each cluster, was tested as an alternative clustering procedure. The results show that membership values, which are an extra output of the fuzzy classification, are a useful indicator of how well a particular household fits in a given cluster. Such information is useful when choosing households to use for agricultural technology testing.
AB - Most household classifications use hard classification procedures that limit a household to only one cluster. In this paper, fuzzy classification, in which individuals can belong totally, partially or not at all to a particular cluster, with membership showing how well they fit in each cluster, was tested as an alternative clustering procedure. The results show that membership values, which are an extra output of the fuzzy classification, are a useful indicator of how well a particular household fits in a given cluster. Such information is useful when choosing households to use for agricultural technology testing.
U2 - 10.5367/000000010791169961
DO - 10.5367/000000010791169961
M3 - Article
SN - 0030-7270
VL - 39
SP - 57
EP - 63
JO - Outlook on Agriculture
JF - Outlook on Agriculture
IS - 1
ER -