Using integrated city data and machine learning to identify and intervene early on housing-related public health problems
K Robb, ND Amigo, A Marcoux… - Journal of Public …, 2022 - journals.lww.com
Objective: The objective of this study was to determine whether machine learning algorithms
can identify properties with housing code violations at a higher rate than inspector-informed …
can identify properties with housing code violations at a higher rate than inspector-informed …
Further Inspection: Leveraging Housing Inspectors and City Data to Improve Public Health in Chelsea, MA
K Robb - 2019 - search.proquest.com
Substandard housing represents an important and growing public health problem. It is
associated with higher rates of mental illness, chronic and infectious disease, and other …
associated with higher rates of mental illness, chronic and infectious disease, and other …
[图书][B] Unravelling the Spatial Distribution of Individual-Level Abandoned Houses at Large Scale Using Open-Access Remotely Sensed Data
S Zou - 2022 - search.proquest.com
Abandoned houses (AH) perform as focal points in declining urban communities by
negatively influencing urban security, housing markets, and government finance in US …
negatively influencing urban security, housing markets, and government finance in US …
인천구도심의공‧ 폐가발생촉발요인과도시계획적대응방안
이다예 - 2018 - s-space.snu.ac.kr
최근 인구 감소와 도시 쇠퇴 현상이 가속화되면서 공‧ 폐가 문제가 새로운 사회 문제로 부상하고
있다. 공‧ 폐가가 근린에 부정적인 영향을 미친다는 점이 강조되면서 공‧ 폐가 문제를 해소하기 …
있다. 공‧ 폐가가 근린에 부정적인 영향을 미친다는 점이 강조되면서 공‧ 폐가 문제를 해소하기 …
Exploration of Algorithmic Bias in Machine Learning Methods Used to Predict Vacancy Rates
KA Amandolia - 2021 - cdr.lib.unc.edu
This project brings the discussion of machine learning algorithms and the potential
associated bias to planning practitioners. This is accomplished by building machine learning …
associated bias to planning practitioners. This is accomplished by building machine learning …