Results 51 to 60 of about 940,524 (345)

Evidence accumulation clustering using combinations of features

MethodsX, 2020
: Evidence accumulation clustering (EAC) is an ensemble clustering algorithm that can cluster data for arbitrary shapes and numbers of clusters. Here, we present a variant of EAC in which we aimed to better cluster data with a large number of features ...
William Wong, Naotsugu Tsuchiya
doaj   +1 more source

K-Means Clustering with Local Distance Privacy

Big Data Mining and Analytics, 2023
With the development of information technology, a mass of data are generated every day. Collecting and analysing these data help service providers improve their services and gain an advantage in the fierce market competition.
Mengmeng Yang, Longxia Huang, Chenghua Tang   +2 more
doaj   +1 more source

Relational Algorithms for k-means Clustering

CoRR, 2020
This paper gives a k-means approximation algorithm that is efficient in the relational algorithms model. This is an algorithm that operates directly on a relational database without performing a join to convert it to a matrix whose rows represent the data points.
Moseley, Benjamin, Pruhs, Kirk, Samadian, Alireza, Wang, Yuyan   +3 more
openaire   +4 more sources

PROCESS CHARACTERISTICS ESTIMATION IN WEB APPLICATIONS USING K-MEANS CLUSTERING [PDF]

Научно-технический вестник информационных технологий, механики и оптики, 2020
Subject of Research. The paper presents the study of estimation problem of process characteristics for the particular case of user’s activity prediction in computer online games.
Victor V. Evstratov, Mikhail S. Ananyevskiy   +1 more
doaj   +1 more source

K−Means Clustering Microaggregation for Statistical Disclosure Control

, 2012
This paper presents a K-means clustering technique that satisfies the bi-objective function to minimize the information loss and maintain k-anonymity. The proposed technique starts with one cluster and subsequently partitions the dataset into two or more
Abdun Naser Mahmood, Abdul K. Mustafa, Kabir, Md Enamul, Mustafa, Abdul K., Md. Enamul Kabir, Mahmood, Abdur Naser   +5 more
core   +1 more source

Scalability of efficient parallel K-Means [PDF]

, 2009
Clustering is defined as the grouping of similar items in a set, and is an important process within the field of data mining. As the amount of data for various applications continues to increase, in terms of its size and dimensionality, it is necessary ...
Giuseppe Di Fatta, Pettinger, David, Di Fatta, Giuseppe, David Pettinger   +3 more
core   +1 more source

K-means clustering algorithm: a brief review

Academic Journal of Computing & Information Science, 2021
K-means clustering is a very classical clustering algorithm, and it is also one of the representatives of unsupervised learning. It has the advantages of a simple idea, high efficiency, and easy implementation, so it is widely used in many fields ...
Bao Chong
semanticscholar   +1 more source

MACOC: a medoid-based ACO clustering algorithm [PDF]

, 2014
The application of ACO-based algorithms in data mining is growing over the last few years and several supervised and unsupervised learning algorithms have been developed using this bio-inspired approach. Most recent works concerning unsupervised learning
Otero, Fernando E. B., David Camacho, Héctor D. Menéndez, Otero, Fernando E.B., Camacho, David, Menendez, Hector, Menéndez, Héctor D., Fernando E. B. Otero   +7 more
core   +1 more source

A Improving House Price Clustering Results with K-means through the Implementation of One-hot Encoding Pre-processing Technique

Journal of Applied Informatics and Computing
Basic human needs include a house that serves as a place to live and a shelter from everything. In Indonesia, owning a house is still a challenging aspect due to its high price.
Vicka Rizqi Maulani, Mula Agung Barata, Pelangi Eka Yuwita   +2 more
doaj   +1 more source

Patient Data Analysis with the Quantum Clustering Method

Quantum Reports, 2023
Quantum computing is one of the most promising solutions for solving optimization problems in the healthcare world. Quantum computing development aims to light up the execution of a vast and complex set of algorithmic instructions. For its implementation,
Shradha Deshmukh, Bikash K. Behera, Preeti Mulay   +2 more
doaj   +1 more source