Results 71 to 80 of about 30,970,765 (331)
IOP Conference Series: Materials Science and Engineering, 2018 Clustering is a data mining technique used to analyse data that has variations and the number of lots. Clustering was process of grouping data into a cluster, so they contained data that is as similar as possible and different from other cluster objects.
M. Syakur +3 more
semanticscholar +1 more source
A parametric k-means algorithm [PDF]
Computational Statistics, 2007 The k points that optimally represent a distribution (usually in terms of a squared error loss) are called the k principal points. This paper presents a computationally intensive method that automatically determines the principal points of a parametric distribution.
openaire +4 more sources
k-Means+++: Outliers-Resistant Clustering
, 2020 The k-means problem is to compute a set of k centers (points) that minimizes the sum of squared distances to a given set of n points in a metric space. Arguably, the most common algorithm to solve it is k-means++ which is easy to implement and provides a
Feldman, Dan +5 more
core +1 more source
, 2021 Machine learning algorithms are an important measure with which to perform landslide susceptibility assessments, but most studies use GIS-based classification methods to conduct susceptibility zonation.
Zizheng Guo +4 more
semanticscholar +1 more source
A Novel K-Means Clustering Algorithm with a Noise Algorithm for Capturing Urban Hotspots
Applied Sciences, 2021 With the development of cities, urban congestion is nearly an unavoidable problem for almost every large-scale city. Road planning is an effective means to alleviate urban congestion, which is a classical non-deterministic polynomial time (NP) hard ...
Xiao-Juan Ran +4 more
semanticscholar +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 +3 more
core +1 more source
Penggunaan N-mers Frequency pada Analisis Barisan DNA
Jambura Journal of Mathematics, 2020 Salah satu metode untuk menganalisis barisan DNA adalah menggunaan N-mers Frequency. N-mers Frequency termasuk metode data mining pada barisan DNA, dimana barisan DNA yang merupakan data string “ACGT” akan diubah menjadi data numerik.
Khoirul Umam, Rahmat Sagara
doaj +1 more source
Binning-Based Silhouette Approach to Find the Optimal Cluster Using K-Means
IEEE Access, 2022 Clustering is one of the critical parts of machine learning algorithms. K-Means clustering is the standard technique that various data analysts use for clustering the data among the various clusters.
Akash Punhani +3 more
semanticscholar +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Adolescents with high‐risk cancer face complex developmental, psychosocial, and ethical challenges that extend beyond disease‐directed treatment. Although international recommendations exist for communication, psychosocial care, pediatric palliative care, survivorship, and shared decision‐making, these have largely evolved within ...
Johanna M. C. Blom +15 more
wiley +1 more source