The package implements two iterative techniques called T3Clus and 3Fkmeans, aimed at simultaneously clustering objects and a factorial dimensionality reduction of variables and occasions on three-mode datasets developed by \(\href{https://doi.org/10.1007/s00357-007-0006-x}{\text{Vichi et. al}}\) in 2007. Also, we provide a convex combination of these two simultaneous procedures called CT3Clus and based on a hyperparameter \(\alpha\) (\(\alpha \in [0,1]\), with 3FKMeans for \(\alpha=0\) and T3Clus for \(\alpha=1\)) was also developed in \(\href{https://doi.org/10.1007/s00357-007-0006-x}{\text{Vichi et. al}}\). Furthermore, we implemented the traditional tandem procedures of T3Clus (TWCFTA) and 3FKMeans (TWFCTA) for sequential clustering-factorial decomposition (TWCFTA), and vice-versa (TWFCTA) proposed by \(\href{https://doi.org/10.1007/978-3-642-79999-0_1}{\text{P. Arabie and L. Hubert}}\) in 1996.
| source codes | publication |
|---|---|
| Python (Github) | PyPI |
| R (Github) | R-CRAN |
In this study, we conducted a case study on improving the National Health Insurance Scheme (NHIS) coverage in the Sunyani municipality. We used the Contingent Valuation Method (CVM), a technique for estimating the Willingness To Pay (WTP) for non-market goods, to determine individuals' willingness to pay for an extension of NHIS coverage. We also employed Binary Logit Regression analysis to identify factors that influence individuals' decisions to pay for an improved NHIS, and included a social interaction term in the model to measure the impact of other individuals' views on an individual's decision. Our research results showed that a majority of NHIS holders who purchase additional drugs when visiting a health facility were willing to pay for an extension of NHIS coverage. The most costly medical conditions for which respondents usually purchased additional drugs and were willing to pay an additional premium for inclusion in NHIS coverage were rehabilitation conditions (such as vision, hearing, and dental issues), cancer, and heart-related surgeries. On average, respondents were willing to pay no more than GH₵30.00 per year to cover these conditions. We recommended that policymakers or planners consider income, gender, and level of education when making NHIS coverage improvement decisions, as these variables were found to be the most significant in our model.
In this work, we developed and implemented five models, TWCFTA, TWFCTA, T3Clus, 3FKMeans, and CT3Clus, in the simuclustfactor packages in Python and R for the analysis of three-mode datasets. These models were proposed by \(\href{https://doi.org/10.1007/s00357-007-0006-x}{\text{Vichi et al.}}\) in 2007 as an alternative to traditional tandem models for simultaneously clustering objects and reducing the dimensionality of variables and occasions in three-mode datasets. T3Clus and 3Fkmeans are iterative techniques that apply the Tucker2 algorithm and K-means algorithm sequentially, while CT3Clus is a convex combination of these two methods with a hyperparameter alpha \((0 \leq \alpha \leq 1)\) that allows for the interpolation between the two. In contrast, tandem analysis only involves the sequential application of clustering and factorial methodologies. We tested these simultaneous models on synthetic and real datasets and found that they produced more well-separated clusters with higher cohesion within clusters, and were better at recovering object-cluster, variable/occasion-factor associations compared to the tandem models. The best results in terms of well-separated clusters with high cohesion within the clusters were obtained when the factorial analysis was prioritized, minimizing the within-cluster deviation of the component scores (i.e. WSS in the reduced space).
University of Aveiro
(Aveiro, Portugal)
MSc. Mathematics & Applications
August 2021 - Sept. 2022
core courses :
supervisor:
University of L'Aquila
(L'Aquila, Italy)
MSc. Mathematical Engineering
July 2020 - July 2021
core courses :
supervisor:
University of Energy and Natural Resources
(Sunyani, Ghana)
BSc. Actuarial Science
August 2019 - September 2020
core courses:
supervisor:
Achimota Senior High
(Accra, Ghana)
General Science
August 2011 - September 2014
core courses:
Python Software Foundation (PSF)
(Sunyani, Ghana)
Team Lead
June 2019 - Date
core activities:
University of Energy & Natural Resources
(Sunyani, Ghana)
Teaching Assistant
September 2019 - September 2020
core activities:
New Fountain International School
(Tema, Ghana)
Pupils Tutor
2014 - 2015
core activities:
IFCS 2022
(University of Porto, Portugal)
17th Conference of the International Federation of Classification Societies
July 2022
Contributed session
Machine Learning in Science
(University of Lisbon, Portugal)
Workshop of Machine Learning in Science
June 2022
participant
core topics:
core topics:
core topics:
core topics:
core topics:
case study of AI in:
Outline:
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