Please use this identifier to cite or link to this item:
http://localhost:8080/xmlui/handle/123456789/1001Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Patil, P. P. | - |
| dc.contributor.author | Banait, S. S. | - |
| dc.date.accessioned | 2018-05-30T10:13:35Z | - |
| dc.date.available | 2018-05-30T10:13:35Z | - |
| dc.date.issued | 2017-12 | - |
| dc.identifier.issn | 2321-9653 | - |
| dc.identifier.uri | http://192.168.3.232:8080/jspui/handle/123456789/1001 | - |
| dc.description.abstract | To reduce computational overhead in processing high dimensional dataset, dimensionality reduction is important mechanism to remove redundant and unused attributes from dataset in data analysis phase. Feature selection and feature extraction are two techniques in dimensionality reductions. This work aims to study various techniques involved in feature subset generation and reduction of data set size, its efficiency in terms of execution time and quality analysis parameters. | en_US |
| dc.publisher | International Journal for Research in Applied Science & Engineering Technology | en_US |
| dc.subject | Dimensionality Reduction, Feature Selection, Feature Extraction, Compound Features, Classification, clustering. | en_US |
| dc.title | A Review on Feature Subset Creation Strategies | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | PG - Students | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| document-1.pdf | A Review on Feature Subset Creation Strategies | 184.63 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.