Distance-based clustering methods usually employ Euclidean distance as the proximity
measure. This paper first identifies the best among some partition-based clustering methods …

Distance measures play an important role in cluster analysis. There is no single distance
measure that best fits for all types of the clustering problems. So, it is important to find set of …

The selection of a proper distance function is crucial for analyzing the data efficiently. To find
an appropriate distance for clustering algorithm is an unsolved problem as of now. The …

Distance measure plays a vital role in clustering algorithms. Selecting the right distance
measure for a given dataset is a challenging problem. In this paper, the effect of six distance …

Clustering is the process of grouping the data based on their similar properties. Meanwhile,
it is the categorization of a set of data into similar groups (clusters), and the elements in each …

Clustering plays a vital role in the various areas of research like Data Mining, Image
Retrieval, Bio-computing and many a lot. Distance measure plays an important role in …

Clustering is a challenging problem that is commonly used for many applications. It aims at
finding the similarity between data points and grouping similar ones into the same cluster. In …

Unsupervised learning is the process to partition the given data set into number of clusters
where similar data objects belongs same cluster and dissimilar data objects belongs to …

As an unsupervised pattern classification method, clustering partitions the input datasets into
groups or clusters. It plays an important role in identifying the natural structure of the target …

Clustering is an unsupervised data mining technique used to determine the objects that are
similar in characteristics and group them together. K-means is a widely used partitional …