Results 41 to 50 of about 9,019,139 (162)
On the Consistency of Metric and Non-Metric K-medoids
, 2020 We establish the consistency of K-medoids in the context of metric spaces. We start by proving that K-medoids is asymptotically equivalent to K-means restricted to the support of the underlying distribution under general conditions, including a wide selection of loss functions. This asymptotic equivalence, in turn, enables us to apply the work of Parna
He Jiang, Ery Arias-Castro
openaire +3 more sources
Active Distance-Based Clustering Using K-Medoids [PDF]
, 2016 k-medoids algorithm is a partitional, centroid-based clustering algorithm which uses pairwise distances of data points and tries to directly decompose the dataset with $n$ points into a set of $k$ disjoint clusters. However, k-medoids itself requires all distances between data points that are not so easy to get in many applications.
Mehrdad Ghadiri +2 more
openaire +3 more sources
Comparison Of K-Means and K-Medoids Algorithm for Clustering Data UMKM in Pagar Alam City
Jurnal SisfokomThe aim of this research is clustering MSME data in Pagar Alam City using the K-Means and K-Medoids algorithms. This research is motivated by the lack of further management of MSME data collection, which can hinder the development and improvement of ...
sendy ariska +2 more
doaj +1 more source
, 2023 Data mining merupakan pemrosesan informasi yang dapat dilakukan secara tersembunyi dari suatu database. Penggunaan data mining banyak sekali diterapkan dalam berbagai sector kehidupan.
Rahayu, Sherly +3 more
core
Efficient approaches for solving the large-scale k-medoids problem [PDF]
, 2017 In this paper, we propose a novel implementation for solving the large-scale k-medoids clustering problem. Conversely to the most famous k-means, k-medoids suffers from a computationally intensive phase for medoids evaluation, whose complexity is ...
Alessio Martino +5 more
core +1 more source
A QUBO Formulation of the k-Medoids Problem
, 2022 5463We are concerned with k-medoids clustering and propose aquadratic unconstrained binary optimization (QUBO) formulation of the problem of identifying k medoids among n data points without having to cluster the data.
Hecker, Dirk +4 more
core +1 more source
Frontiers in Earth Science, 2022 Rockbursts occur in many deep underground excavations and have caused non-negligible casualties or property losses in deep underground building activities over the past hundreds of years.
Zhenzhao Xia, Jingyin Mao, Yao He
doaj +1 more source
Business Strategy and the Environment, EarlyView.ABSTRACT This study examines how plastics manufacturing firms can be classified according to their level of implementation of circular economy (CE) and industrial symbiosis (IS) practices and how such adoption influences sustainability performance. Using data from plastics manufacturing firms, we integrate cluster analysis with partial least squares ...
Laura Cristina Ramírez‐Rodríguez +3 more
wiley +1 more source
Business Strategy and the Environment, EarlyView.ABSTRACT The rapid digital transformation of financial services, increasing regulatory pressure and the growing strategic relevance of sustainability are reshaping financial intermediaries and how they are perceived by younger generations. In this context, traditional monetary compensation schemes are increasingly insufficient to explain how financial ...
Gerardo Petroccione +2 more
wiley +1 more source
Volume-profit relationship of LRFMV model for K-Medoids algorithm.
, 2022 Volume-profit relationship of LRFMV model for K-Medoids algorithm.
Rezwana Mahfuza (14285061) +5 more
core +1 more source