PropertyValue
?:abstract
  • Using a dwelling of an appropriate standard is one of the basic needs of a household. Therefore, studying various dimensions of housing poverty, including overcrowding, has recently gained importance. The aim of the study is to investigate housing overcrowding and socioeconomic factors associated with it in four countries of Central Europe: the Czech Republic (Czechia), Hungary, Poland and Slovakia, known as the Visegrad Group (V4). The latest statistical data on income and living conditions (EU-SILC) for 2022 was used. The study is based on machine learning algorithms such as Random Forests, Balanced Random Forests, Extreme Gradient Boosting and a relatively new method, CatBoost, which has recently gained much attention and has not yet been used to study the issue of housing overcrowding. It was found that CatBoost exhibits the best classification performance in terms of accuracy and Area Under the Curve (AUC). Based on the results obtained using the CatBoost method, it was found that the following characteristics are of great importance: household type, apartment type, property status, age, and education of household members. The analyzes performed also revealed that, apart from various characteristics of households, the country of residence has a significant impact on the occurrence of overpopulation. (xsd:string)
?:author
?:comment
  • (SILC) (xsd:string)
?:dataSource
  • EU-SILC-Bibliography (xsd:string)
?:dateModified
  • 2024 (xsd:gyear)
?:datePublished
  • 2024 (xsd:gyear)
?:doi
  • 10.1016/j.procs.2024.09.294 ()
?:fromPage
  • 4441 (xsd:string)
is ?:hasPart of
?:inLanguage
  • english (xsd:string)
?:isPartOf
?:issn
  • 18770509 ()
?:name
  • Socioeconomic factors associated with household overcrowding in the Visegrad Group countries – analysis based on machine learning approach (xsd:string)
?:publicationType
  • article (xsd:string)
?:reference
?:sourceInfo
  • Bibsonomy (xsd:string)
  • In Procedia Computer Science, 246, 4441-4450, 2024 (xsd:string)
?:studyGroup
  • European Union Statistics on Income and Living Conditions (EU-SILC) (xsd:string)
?:tags
  • 2024 (xsd:string)
  • FDZ_GML (xsd:string)
  • SILC (xsd:string)
  • SILC_input2024 (xsd:string)
  • SILC_pro (xsd:string)
  • article (xsd:string)
  • english (xsd:string)
  • indexproved (xsd:string)
  • noindex (xsd:string)
  • qq (xsd:string)
  • review_proved (xsd:string)
  • transfer24 (xsd:string)
?:toPage
  • 4450 (xsd:string)
rdf:type
?:url
?:volumeNumber
  • 246 (xsd:string)