Noise Removal Techniques using Data Analysis in Data Mining

  Byalalli Rajeshri

Data mining is the process of extraction of relevant information from data warehouse. It also refers to the analysis of the data using pattern matching techniques. Presently, a very large amount of data stored in databases. This requires a need for new techniques and tools to aid humans in automatically and intelligently analyzing large data sets to acquire useful information. Removing objects that are noise is an important goal of data cleaning. Because data sets can contain large amount of noise, these techniques also need to be able to discard a potentially large fraction of the data. This paper presents, a different data cleaning methods to focus on removing noise includes in Data mining. Thus, if the goal is to enhance the data analysis as much as possible, these objects should be considered as noise, at least with respect to the underlying analysis.

Keywords- Data Mining, Data Analysis, Noise Removal

Unique Identification Number - IJEDR1503102
Page Number(s) - 1-3
Pubished in - Volume 3 | Issue 3 | September 2015
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  Byalalli Rajeshri,   "Noise Removal Techniques using Data Analysis in Data Mining", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.3, Issue 3, pp.1-3, September 2015, Available at :http://www.ijedr.org/papers/IJEDR1503102.pdf