The objective of this report is the analysis of the data arising from the Family Lifestyles survey conducted by the University of Bari “A. Moro” (2012-2013) through the construction of indicators of socio-economic hardship and the identification of family profiles during the current period of crisis. The approach used in this work in order to synthesize and measure the conditions of hardship of a population is based on the so-called “Totally Fuzzy and Relative” method employing a Fuzzy Sets technique in order to obtain a measure of relative incidence in a population from the statistical information provided by a plurality of indicators [1]. The subsequent step involved considering a clustering procedure (Fuzzy c-means) with the objective of outlining various profiles, not defined a priori, to be assigned to each family with different socioeconomic behaviours [2]. This clustering method allows, compared to conventional methods, a set of data to belong not

The Lifestyles of Families through Fuzzy C-Means Clustering

PERCHINUNNO Paola;MONTRONE Silvestro;L'ABBATE Samuela;ZITOLO Maria Rosaria
2014-01-01

Abstract

The objective of this report is the analysis of the data arising from the Family Lifestyles survey conducted by the University of Bari “A. Moro” (2012-2013) through the construction of indicators of socio-economic hardship and the identification of family profiles during the current period of crisis. The approach used in this work in order to synthesize and measure the conditions of hardship of a population is based on the so-called “Totally Fuzzy and Relative” method employing a Fuzzy Sets technique in order to obtain a measure of relative incidence in a population from the statistical information provided by a plurality of indicators [1]. The subsequent step involved considering a clustering procedure (Fuzzy c-means) with the objective of outlining various profiles, not defined a priori, to be assigned to each family with different socioeconomic behaviours [2]. This clustering method allows, compared to conventional methods, a set of data to belong not
2014
978-3-319-09149-5
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11586/114775
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