Cluster analysis is the assignment of observations into clusters so that observations in the same cluster are similar in some sense, and many clustering methods have been developed. However, these methods cannot be applied to family data, which possess intrinsic familial structure. To take the familial structure into account, we propose a form of penalized cluster analysis with a tuning paramet...

Trajectory clustering has played a crucial role in data analysis since it reveals underlying trends of moving objects. Due to their sequential nature, trajectory data are often received incrementally, e.g., continuous new points reported by GPS system. However, since existing trajectory clustering algorithms are developed for static datasets, they are not suitable for incremental clustering wit...

— Clustering ensemble is one of the most recent advances in unsupervised learning. It aims to combine the clustering results obtained using different algorithms or from different runs of the same clustering algorithm for the same data set, this is accomplished using on a consensus function, the efficiency and accuracy of this method has been proven in many works in literature. In the first part...

AMA Selskyy P, Sverstiuk A, Slyva Selskyi B. Prediction of the progression endometrial hyperplasia in women premenopausal and menopausal age based on an analysis clinical anamnestic indicators using multiparametric neural network clustering. Family Medicine & Primary Care Review. 2023;25(2):184-189. doi:10.5114/fmpcr.2023.127679. APA Selskyy, P., Sverstiuk, A., Slyva, Selskyi, (2023). Review, 2...

MOTIVATION UPGMA (average linking) is probably the most popular algorithm for hierarchical data clustering, especially in computational biology. However, UPGMA requires the entire dissimilarity matrix in memory. Due to this prohibitive requirement, UPGMA is not scalable to very large datasets. APPLICATION We present a novel class of memory-constrained UPGMA (MC-UPGMA) algorithms. Given any pr...

A protein family contains sequences that are evolutionarily related. Generally, this is reflected by sequence similarity. There have been many attempts to organize the set of protein families into evolutionarily homogenous clusters using certain clustering methods. How do we characterize these clusters? How can we cluster protein families using these characterizations? In this work, these quest...

— Nowadays, overseas commerce has increased drastically in many countries. Plenty fruits are imported from the other nations such as oranges, apples etc. Manual identification of defected fruit is very time consuming. This work presents a novel defect segmentation of fruits based on color features with K-means clustering unsupervised algorithm. We used color images of fruits for defect segmenta...