Performance Analysis of Clustering using Partitioning and Hierarchical Clustering Techniques

Punitha, S.; Ranjith, P; Thangaiah, Jeba; Punithavalli, M.; Ramakrishna, Sri

doi:10.14257/ijdta.2014.7.6.21

Cited by 6 publications

(2 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Nowadays information filtering and information retrieving from the large available information have a great attention to the both domestic and International consumers. [1][2] Document clustering aims to group the same category documents into a single clusters, it is one of the most important tasks in data mining and artificial intelligence that are having a much importance in recent years. The main aspects is to cluster forming with a high accuracy as needed.…”

Section: Text Classificationmentioning

confidence: 99%

Smart Learning in Document Categorization using Dynamic Learning

2019

IJRTE

View full text Add to dashboard Cite

Clustering is the process of making data groups using similar data items, used for data mining to extract data from available large datasets. A large volume of text documents consisting of personal information is being generated in form of digital libraries and repositories in internet daily.It is conceivable to get to great quality instructive substance and strategies in an increasingly helpful manner. In spite of the fact that a ton of keen instruments have been connected for instructive application, there are just restricted looks into that show the instructive viability of shrewd devices through test contemplations, Clustering organizes large quantity of unordered text documents into small number of meaningful and coherent clusters. A clustering method based on K-Means algorithm is proposed in this paper. K-Means is a unsupervised algorithm based on randomly selected initial centroids used to cluster a highly unstructured and unlabeled document collection. The system will be evaluated using precision as a measure.

show abstract

Section: Text Classificationmentioning

confidence: 99%

Smart Learning in Document Categorization using Dynamic Learning

2019

IJRTE

View full text Add to dashboard Cite

show abstract

“…K-Means is one of the simplest unsupervised learning algorithms to classify a given data set through a certain number of clusters fixed a priori [14]. The term "k-means" was first used by James MacQueen in 1967, though the idea goes back to 1957.…”

Section: K-means Clusteringmentioning

confidence: 99%

Stress Analysis of Pressure Vessel Clustering Analysis of Simple K – Means Algorithm for Various Data Sets in Function Optimization Problem (Fop) of Evolutionary Programming Different Type of End Connections by FEA

Karthick¹

2015

IJIRSET

View full text Add to dashboard Cite

Evolutionary Algorithms are based on some influential principles like Survival of the Fittest and with some natural phenomena in Genetic Inheritance. The key for searching the solution in improved function optimization problems are based only on Selection and Mutation operators. In this paper a Selection algorithm for data set is chosen so as to identify the survival of the fittest and also the simple K means clustering algorithm is analyzed on different data sets to check for the performance of the K -means on different data set which gives best accuracy to identify the best solution.

show abstract