K-means clustering algorithm is implemented on 87 eligible models, out of a repository of 1000 models, and classifies them to corollary clusters that correspond to complexity levels. By assigning weighted impact on specific complexity metrics -an action that leads to the production of threshold ...
Complexity Analysis We can implement K-means algorithm in pseudo-code: K-MEANS(K, t, s): //The paramaters denote the number of clusters, the iteration times and the dataset respectively Initialize c[K] //Denote the centroid set while t for i in s min_dist = INF for j = 1 to K...
The day to day computation has made the data sets and data objects to grow large so it has become important to cluster the data in order to reduce complexity to some extent. K-means clustering algorithm is an efficient clustering algorithm to cluster the data, but the problem with the k-...
Abstract:K-means algorithm is the clustering algorithm based on the distance as the similarity measure. But the traditional K-means algorithm are difficult to determine the center number, and greatly influenced by the noise and outliers. This paper uses the between class and within class dissimilari...
Advantages of the K-means clustering algorithm include its simplicity, low computational complexity, fast convergence speed, and ability to quickly process large-scale datasets (Chen et al., 2020). However, this method presents certain shortcomings. For example, the number of clusters K must be sp...
On the basis of summarizing and analyzing previous research works, this paper expounded the current research status and significance of financial risk early-warning, elaborated the development background, current status and future challenges of the K-means clustering algorithm, introduced the related ...
"Enhancing K-means clustering algorithm with improved initial centers",International Journal of Computer Science and information Technologies. Vol.1(2), 121-125,2010.Yedla,Pathakota & Srinivasa, Enhancing K-Means Clustering Algorithm with Improved Initial Center, International Journal of Computer Science...
1 K-means指纹定位 K-means指纹定位是在原指纹定位算法的基础上,先对指纹库进行聚类分析,再通过匹配算法估计待测点位置的一种算法。即离线阶段,构建指纹库后,通过K-means聚类根据特征参数将指纹库划分为k个子库;匹配阶段,首先比较待测点与各聚类中心的相似程度,选取距离最短的聚类中心所在的子库,再将其与待测点...
This paper proposes a privacy-preserving k-means clustering algorithm that utilizes the proposed decimal-based encryption operation protocols. While providing superior processing performance, the proposed k-means clustering algorithm ensures that data, queries, and data access patterns are safeguarded in or...
In our paper for the purpose of initializing the initial centroids of the Improved Hybridized K Means clustering algorithm (IHKMCA) we make use of genetic algorithm, so as to get a more accurate result. The results thus found from the proposed work have better accuracy, more efficient and ...