Application of classification technique in healthcare is challenging because of high
dimensional medical data and of its dynamic nature. The research work here is focused on …

In data mining or machine learning clustering is very broad area. Clustering is a technique
which decomposes the data set into different cluster. There are many clustering algorithms …

Big data analytics examines large amounts of data to uncover hidden patterns, correlations
and other insights. Clustering is the task of dividing the population or data points into a …

Medical data mining is the process of extracting hidden patterns from medical data. Among
the various clustering algorithms, k-means is the one of most widely used clustering …

Clustering Performance is based iterative and analysis is a descriptive task that seeks to
identify homogeneous groups of objects based on the values of the methodology is search …

In this paper we propose an efficient algorithm that is based on divide and conquers
technique for clustering the large datasets. In our research work we have applied divide and …

In Indonesia, tuberculosis remains one of the major health problems unresolved. Indonesia
is second ranked in the world as the country with the most tuberculosis cases. The purpose …

Data mining is the process of extract information from a large data set and transform it into
an understandable form for further use. Clustering is important in data analysis and data …

The set of objects having same characteristics are organized in groups and clusters of these
objects reformed known as Data Clustering. It is an unsupervised learning technique for …

Clustering algorithms based on partitions are widely us ed in unsupervised data analysis. K-
means algorithm is one the efficient partition based algorithms ascribable to its intelligibility …