A comparative study of K-Means, DBSCAN and OPTICS
HK Kanagala, VVJR Krishnaiah - … International Conference on …, 2016 - ieeexplore.ieee.org
In view of today's information available, recent progress in data mining research has lead to
the development of various efficient methods for mining interesting patterns in large …
the development of various efficient methods for mining interesting patterns in large …
Collaborative filtering-based recommendations against shilling attacks with particle swarm optimiser and entropy-based mean clustering
Recommender system (RS) in the present web environment is required to gain the
knowledge of the users and their commitments such as like and dislike about any items …
knowledge of the users and their commitments such as like and dislike about any items …
Association of Data Mining and Biomedical Domain: Choosing the Best Algorithm for Analysis
DV Chandra Shekar, VV Jaya Rama Krishnaiah… - 2013 - indianjournals.com
Data mining has been used prosperously in the favourably perceived areas, such as e-
business, marketing, health domain and retail, because of which it is now applicable in …
business, marketing, health domain and retail, because of which it is now applicable in …
An Efficient Selection of Initial Cluster in K-Means Using Entropy and Co-efficient of Variation for High Dimensional Data.
P Krishnakumari, P Gokila - International Journal of …, 2012 - search.ebscohost.com
K-means clustering is a method of cluster analysis which aims to partition n observations
into k-clusters in which each observation belongs to the cluster with the nearest mean. For …
into k-clusters in which each observation belongs to the cluster with the nearest mean. For …