Open AccessAn analysis of modified naïve Bayesian classification using correlation based clustering for gene sequence data analysis
Author(s) -
Vijay Arputharaj J,
S. Sheeja
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i4.5.21169
Subject(s) - cluster analysis , computer science , curse of dimensionality , artificial intelligence , pattern recognition (psychology) , data mining , correlation , consensus clustering , sequence (biology) , single linkage clustering , bayesian probability , clustering high dimensional data , correlation clustering , cure data clustering algorithm , mathematics , geometry , biology , genetics
Correlation based Clustering separates the statistical data into the most favorable amount of clusters on the correspondence to the statisti- cally analyzed data points. As we know that, Data mining is the technique of figuring out the progression of determines patterns inside huge statistics and data sets which concerning on techniques on the connection with machine related learning, statistics and also the advanced database systems. this technique denotes the gene sequence by using the novel classification technique, which improves the accuracy of classification under the curse of dimensionality, also clustering the gene data based on correlation based clustering will re- duce the execution time.