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A Systematic Literature Review of Data Classification Techniques
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 177 - Number 44 |
| Year of Publication: 2020 |
| Authors: Neha Nigam, Anand Rajavat |
10.5120/ijca2020919971
|
Neha Nigam, Anand Rajavat . A Systematic Literature Review of Data Classification Techniques. International Journal of Computer Applications. 177, 44 ( Mar 2020), 41-44. DOI=10.5120/ijca2020919971
Abstract
The data mining and their different applications are becomes more popular now in these days a number of large and small scale applications are developed with the help of data mining techniques i.e. predictors, regulators, weather forecasting systems and business intelligence. Many of classification algorithms are available to analyze data. Classification is used to classify each item in a data set into one of a predefined set of classes or groups. Classification is the chore of identifying a model or function. There are two kinds of model are available for namely supervised and unsupervised. The performance and accuracy of the supervised data mining techniques are higher as compared to unsupervised techniques therefore in sensitive applications the supervised techniques are used for prediction and classification. In this presented work the supervised learning based data mining techniques for classification and prediction are analyzed.
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