Cluster analysis of mixed and missing chronic kidney disease data in KwaZulu-Natal Province, South Africa
Real-world datasets, particularly Electronic Health Records, are routinely found to be mixed
(comprised of both categorical and continuous variables) and/or missing in nature. Such …
(comprised of both categorical and continuous variables) and/or missing in nature. Such …
The deep kernelized autoencoder
Autoencoders learn data representations (codes) in such a way that the input is reproduced
at the output of the network. However, it is not always clear what kind of properties of the …
at the output of the network. However, it is not always clear what kind of properties of the …
Fuzzy clustering method with approximate orthogonal regularization
As a widely used unsupervised learning method, clustering model plays an indispensable
role in exploring data structures. Spectral analysis is a useful technique for clustering …
role in exploring data structures. Spectral analysis is a useful technique for clustering …
An unsupervised multivariate time series kernel approach for identifying patients with surgical site infection from blood samples
A large fraction of the electronic health records consists of clinical measurements collected
over time, such as blood tests, which provide important information about the health status of …
over time, such as blood tests, which provide important information about the health status of …
Advancing Segmentation and Unsupervised Learning Within the Field of Deep Learning
MC Kampffmeyer - 2018 - munin.uit.no
Due to the large improvements that deep learning based models have brought to a variety of
tasks, they have in recent years received large amounts of attention. However, these …
tasks, they have in recent years received large amounts of attention. However, these …
Link-based cluster ensemble method for improved meta-clustering algorithm
C Shao, S Ding - Intelligent Information Processing X: 11th IFIP TC 12 …, 2020 - Springer
Ensemble clustering has become a hot research field in intelligent information processing
and machine learning. Although significant progress has been made in recent years, there …
and machine learning. Although significant progress has been made in recent years, there …
Fuzzy smooth equilibrium method for clustering
J Yang, Z Yang - International Journal of Fuzzy Systems, 2020 - Springer
Clustering model plays an indispensable role in exploring data structures. To extend
supervised learning to unsupervised, the maximum margin clustering model has been …
supervised learning to unsupervised, the maximum margin clustering model has been …
[PDF][PDF] Cluster Analysis of Mixed and Missing Chronic Kidney Disease Data in KwaZulu-Natal Province, South Africa
AG ASSOUNGA - academia.edu
Real-world datasets, particularly Electronic Health Records, are routinely found to be mixed
(comprised of both categorical and continuous variables) and/or missing in nature. Such …
(comprised of both categorical and continuous variables) and/or missing in nature. Such …
Advancing Unsupervised and Weakly Supervised Learning with Emphasis on Data-Driven Healthcare
KØ Mikalsen - 2019 - munin.uit.no
In healthcare, vast amounts of data are stored digitally in the electronic health records
(EHRs). EHRs represent a largely untapped source of clinically relevant information, which …
(EHRs). EHRs represent a largely untapped source of clinically relevant information, which …