title: Unsupervised discretization using tree-based density estimation

authors: Schmidberger, Gabi

subjects: computer science

abstract: This paper presents an unsupervised discretization method that performs density estimation for univariate data. The subintervals that the discretization produces can be used as the bins of a histogram. Histograms are a very simple and broadly understood means for displaying data, and our method automatically adapts bin widths to the data. It uses the log-likelihood as the scoring function to select cut points and the cross-validated log-likelihood to select the number of intervals. We compare this method with equal-width discretization where we also select the number of bins using the cross-validated log-likelihood and with equal-frequency discretization.

text: Unsupervised discretization using tree-based density estimation This paper presents an unsupervised discretization method that performs density estimation for univariate data. The subintervals that the discretization produces can be used as the bins of a histogram. Histograms are a very simple and broadly understood means for displaying data, and our method automatically adapts bin widths to the data. It uses the log-likelihood as the scoring function to select cut points and the cross-validated log-likelihood to select the number of intervals. We compare this method with equal-width discretization where we also select the number of bins using the cross-validated log-likelihood and with equal-frequency discretization.

year: 2005

title: COVIDiSTRESS diverse dataset on psychological and behavioural outcomes one year into the COVID-19 pandemic

authors: Blackburn, Angélique M.

abstract: During the onset of the COVID-19 pandemic, the COVIDiSTRESS Consortium launched an open-access global survey to understand and improve individuals’ experiences related to the crisis. A year later, we extended this line of research by launching a new survey to address the dynamic landscape of the pandemic. This survey was released with the goal of addressing diversity, equity, and inclusion by working with over 150 researchers across the globe who collected data in 48 languages and dialects across 137 countries. The resulting cleaned dataset described here includes 15,740 of over 20,000 responses. The dataset allows cross-cultural study of psychological wellbeing and behaviours a year into the pandemic. It includes measures of stress, resilience, vaccine attitudes, trust in government and scientists, compliance, and information acquisition and misperceptions regarding COVID-19. Open-access raw and cleaned datasets with computed scores are available. Just as our initial COVIDiSTRESS dataset has facilitated government policy decisions regarding health crises, this dataset can be used by researchers and policy makers to inform research, decisions, and policy.</jats:p>

text: COVIDiSTRESS diverse dataset on psychological and behavioural outcomes one year into the COVID-19 pandemic During the onset of the COVID-19 pandemic, the COVIDiSTRESS Consortium launched an open-access global survey to understand and improve individuals’ experiences related to the crisis. A year later, we extended this line of research by launching a new survey to address the dynamic landscape of the pandemic. This survey was released with the goal of addressing diversity, equity, and inclusion by working with over 150 researchers across the globe who collected data in 48 languages and dialects across 137 countries. The resulting cleaned dataset described here includes 15,740 of over 20,000 responses. The dataset allows cross-cultural study of psychological wellbeing and behaviours a year into the pandemic. It includes measures of stress, resilience, vaccine attitudes, trust in government and scientists, compliance, and information acquisition and misperceptions regarding COVID-19. Open-access raw and cleaned datasets with computed scores are available. Just as our initial COVIDiSTRESS dataset has facilitated government policy decisions regarding health crises, this dataset can be used by researchers and policy makers to inform research, decisions, and policy.</jats:p>

year: 2022

title: An indigenous psychologies teaching and research hub : Enabling our resources, strengths and histories

authors: Nikora, Linda Waimarie

abstract: This paper was presented as part of an informal indigenous psychologies dialogue session at the Australian Psychological Society's annual conference. In this paper, we present the concept of an indigenous psychologies teaching and research hub that reduces distance, helps students remain in community, uses resources efficiency, and has the capacity to bring indigenous psychologist and academics into closer communication.

text: An indigenous psychologies teaching and research hub : Enabling our resources, strengths and histories This paper was presented as part of an informal indigenous psychologies dialogue session at the Australian Psychological Society's annual conference. In this paper, we present the concept of an indigenous psychologies teaching and research hub that reduces distance, helps students remain in community, uses resources efficiency, and has the capacity to bring indigenous psychologist and academics into closer communication.

year: 2014