Cluster Based Boosting Techniques for Accuracy Prediction
| dc.category | Journal Article | |
| dc.contributor.author | Elizabeth Shanthi, I | |
| dc.date.accessioned | 2017-03-30T00:17:35Z | |
| dc.date.available | 2017-03-30T00:17:35Z | |
| dc.date.issued | 2016 | |
| dc.department | Computer Science | en_US |
| dc.description.abstract | In recent years encroachment of social media in human life is inexplicable. The greatest and most significant issue in latest technology is the fast retrieval of information from large databases. To overcome this, different techniques have been developed. Improving the retrieval process and its accuracy is a vital factor in the predictive analyses of Machine learning. Boosting is one of the techniques used for enhancing the accuracy of prediction in supervised learning. In this process, lot of noise data may arise which adds another problem in handling training data set. Extracting accurate data from the training dataset is an essential factor in applying clustering techniques. This paper surveys the various boosting/clustering techniques and compares them with a motive to suggest a better environment which is free from noise/errors so as to have maximum accuracy on the output data. | en_US |
| dc.identifier.uri | https://ir.avinuty.ac.in/handle/avu/2351 | |
| dc.lang | English | en_US |
| dc.publisher.name | INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY | en_US |
| dc.publisher.type | International | en_US |
| dc.title | Cluster Based Boosting Techniques for Accuracy Prediction | en_US |
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