AIMC Topic: Cluster Analysis

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A novel representation of genomic sequences for taxonomic clustering and visualization by means of self-organizing maps.

Bioinformatics (Oxford, England)
MOTIVATION: Self-organizing maps (SOMs) are readily available bioinformatics methods for clustering and visualizing high-dimensional data, provided that such biological information is previously transformed to fixed-size, metric-based vectors. To inc...

Learning Stable Multilevel Dictionaries for Sparse Representations.

IEEE transactions on neural networks and learning systems
Sparse representations using learned dictionaries are being increasingly used with success in several data processing and machine learning applications. The increasing need for learning sparse models in large-scale applications motivates the developm...

Support Vector Feature Selection for Early Detection of Anastomosis Leakage From Bag-of-Words in Electronic Health Records.

IEEE journal of biomedical and health informatics
The free text in electronic health records (EHRs) conveys a huge amount of clinical information about health state and patient history. Despite a rapidly growing literature on the use of machine learning techniques for extracting this information, li...

Manifold Adaptive Label Propagation for Face Clustering.

IEEE transactions on cybernetics
In this paper, a novel label propagation (LP) method is presented, called the manifold adaptive label propagation (MALP) method, which is to extend original LP by integrating sparse representation constraint into regularization framework of LP method...

Optimization of a multilayer neural network by using minimal redundancy maximal relevance-partial mutual information clustering with least square regression.

IEEE transactions on neural networks and learning systems
In this paper, an optimized multilayer feed-forward network (MLFN) is developed to construct a soft sensor for controlling naphtha dry point. To overcome the two main flaws in the structure and weight of MLFNs, which are trained by a back-propagation...

Alpha-plane based automatic general type-2 fuzzy clustering based on simulated annealing meta-heuristic algorithm for analyzing gene expression data.

Computers in biology and medicine
This paper considers microarray gene expression data clustering using a novel two stage meta-heuristic algorithm based on the concept of α-planes in general type-2 fuzzy sets. The main aim of this research is to present a powerful data clustering app...

Hodge-Kodaira decomposition of evolving neural networks.

Neural networks : the official journal of the International Neural Network Society
Although it is very important to scrutinize recurrent structures of neural networks for elucidating brain functions, conventional methods often have difficulty in characterizing global loops within a network systematically. Here we applied the Hodge-...

Patterns in Mental Health Symptoms, Substance Use, and Viral Suppression in People with HIV: A Clustering Analysis.

AIDS and behavior
Mental health conditions and substance use are prevalent among people with HIV (PWH), are correlated with one another, and associate with viral non-suppression independently; their joint association with viral non-suppression may be under-studied bec...