From clustering to clustering ensemble selection: A review
Clustering, as an unsupervised learning, is aimed at discovering the natural groupings of a
set of patterns, points, or objects. In clustering algorithms, a significant problem is the …
set of patterns, points, or objects. In clustering algorithms, a significant problem is the …
A comprehensive survey of clustering algorithms: State-of-the-art machine learning applications, taxonomy, challenges, and future research prospects
AE Ezugwu, AM Ikotun, OO Oyelade… - … Applications of Artificial …, 2022 - Elsevier
Clustering is an essential tool in data mining research and applications. It is the subject of
active research in many fields of study, such as computer science, data science, statistics …
active research in many fields of study, such as computer science, data science, statistics …
[HTML][HTML] An ensemble agglomerative hierarchical clustering algorithm based on clusters clustering technique and the novel similarity measurement
T Li, A Rezaeipanah, ESMT El Din - … of King Saud University-Computer and …, 2022 - Elsevier
The advent of architectures such as the Internet of Things (IoT) has led to the dramatic
growth of data and the production of big data. Managing this often-unlabeled data is a big …
growth of data and the production of big data. Managing this often-unlabeled data is a big …
A comprehensive survey of image segmentation: clustering methods, performance parameters, and benchmark datasets
Image segmentation is an essential phase of computer vision in which useful information is
extracted from an image that can range from finding objects while moving across a room to …
extracted from an image that can range from finding objects while moving across a room to …
[图书][B] Statistical pattern recognition
AR Webb - 2003 - books.google.com
Statistical pattern recognition is a very active area of study andresearch, which has seen
many advances in recent years. New andemerging applications-such as data mining, web …
many advances in recent years. New andemerging applications-such as data mining, web …
Cluster analysis and mathematical programming
Given a set of entities, Cluster Analysis aims at finding subsets, called clusters, which are
homogeneous and/or well separated. As many types of clustering and criteria for …
homogeneous and/or well separated. As many types of clustering and criteria for …
Uncovering the socioeconomic facets of human mobility
H Barbosa, S Hazarie, B Dickinson, A Bassolas… - Scientific reports, 2021 - nature.com
Given the rapid recent trend of urbanization, a better understanding of how urban
infrastructure mediates socioeconomic interactions and economic systems is of vital …
infrastructure mediates socioeconomic interactions and economic systems is of vital …
A taxonomy of machine learning clustering algorithms, challenges, and future realms
In the field of data mining, clustering has shown to be an important technique. Numerous
clustering methods have been devised and put into practice, and most of them locate high …
clustering methods have been devised and put into practice, and most of them locate high …
Use of structure− activity data to compare structure-based clustering methods and descriptors for use in compound selection
RD Brown, YC Martin - Journal of Chemical Information and …, 1996 - ACS Publications
An evaluation of a variety of structure-based clustering methods for use in compound
selection is presented. The use of MACCS, Unity and Daylight 2D descriptors; Unity 3D rigid …
selection is presented. The use of MACCS, Unity and Daylight 2D descriptors; Unity 3D rigid …