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Analysis of Prediction Techniques based on Classification and Regression

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Pinki Sagar, Prinima, Indu

Pinki Sagar, Prinima and Indu. Analysis of Prediction Techniques based on Classification and Regression. International Journal of Computer Applications 163(7):47-51, April 2017. BibTeX

	author = {Pinki Sagar and Prinima and Indu},
	title = {Analysis of Prediction Techniques based on Classification and Regression},
	journal = {International Journal of Computer Applications},
	issue_date = {April 2017},
	volume = {163},
	number = {7},
	month = {Apr},
	year = {2017},
	issn = {0975-8887},
	pages = {47-51},
	numpages = {5},
	url = {},
	doi = {10.5120/ijca2017913623},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Data Mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information – making it more accurate, reliable, efficient and beneficial. In data mining various techniques are used- classification, clustering, regression, association mining. These techniques can be used on various types of data; it may be stream data, one dimensional, two dimensional or multi-dimensional data. In this paper we analyze the data mining techniques based on various parameters. All data mining techniques used in various fields for prediction and extraction of useful data or knowledge from a large data base is analyzed and each data mining technique has different performance.


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Data mining, Classification, Prediction, Clustering, Association