资讯

Visual Studio Magazine11 年

K-Means Data Clustering Using C#

Data clustering is the process of placing data items into groups so that items within a group are similar and items in different groups are dissimilar. The most common technique for clustering numeric ...
Visual Studio Magazine11 年

K-Means Data Clustering Using C#

Data clustering is the process of placing data items into groups so that items within a group are similar and items in different groups are dissimilar. The most common technique for clustering numeric ...
Scientific Research Publishing9 天

Application of the K-Means Algorithm in the Study of Influenza Transmission Patterns ()

K-Means Algorithm, Influenza Transmission, Cluster Analysis, Urban Characteristics Share and Cite: Ye, S. (2025) Application ...
TechRepublic3 年

Implementation of an Entropy Weighted K-Means Algorithm for High Dimensional Sparse Data

In this paper, the authors contain a partitional based algorithm for clustering high-dimensional objects in subspaces for iris gene dataset. In high dimensional data, clusters of objects often exist ...
JSTOR Daily1 年

EVALUATION AND COMPARISON OF CLUSTERING ALGORITHMS IN ANALYZING ES CELL GENE EXPRESSION DATA

Statistica Sinica, Vol. 12, No. 1, A Special Issue on Bioinformatics (January 2002), pp. 241-262 (22 pages) Many clustering algorithms have been used to analyze microarray gene expression data. Given ...
Ghanaweb.com6月

How unsupervised machine learning and K-means clustering are shaping consumer insights

Business stakeholders are always looking for innovative ways to better understand customer behaviour in the current, data-driven marketing landscape. Unsupervised machine learning, which allows ...