Clustering of Mixed data: A GKMM approach
Journal Title: International Journal of Advanced Biotechnology and Research. - Year 2016, Vol 7, Issue 2
Abstract
ABSTRACTClustering is important problem in data mining techniques. k-Means algorithm is one of the most capable and easy to employ clustering algorithm but having some difficulties i.e. applicable to numeric data, sensitive to the presence of noise and outliers and have initialisation issues. This paper proposed GKMM algorithm to cluster mixed data where the pre-processed data will be used for the clustering to overcome the limitation of local solution and handle only numeric data issues. This work is based on the concept of utilisation of numeric data based genetics clustering algorithm for mixed data and can be an easier alternative to reduce cost and helpful in optimizing performance. Moreover, decrease obvious sensitivity to the initial guess of the cluster centres.
Authors and Affiliations
Abha Sharma*1 and R. S. Thakur2
The relationship between qualities of services provided to customers with purchase intention at Saderat Bank of Bandar Anzali city
ABSTRACT Reviewing customer purchase intention (whether services or goods) for business firms, including banks that their survival depends on appropriate interaction with customers, is considered important. Customer pu...
DIFFERENTIAL FATTY ACID EXPRESSION IN NATIVE, INJURED AND INFECTED HOUSEFLY - MUSCA DOMESTICA L., LARVAE
MODELING OF AMBIENT FOR SOx AND NOx POLLUTANTS THROUGH ARTIFICAL NEURAL NETWORK IN SENSITIVE AREA OF UJJAIN CITY
A study on the connection and physical properties of Cadmium selenide nanoparticles and zinc sulfide nanoparticles made by ultrasonic method
ABSTRACT Ultrasonic waves are called to hordes of mechanical waves that their oscillation frequency exceeds from human hearing range (20 Hz- 20 KHz). These waves have various applications due to their properties; ultra...
A Simple and Efficient Method for High Quality Genomic DNA Isolation From Cannabis Sativa Containing High Amount Of Polyphenols