Name
Title | ||
|---|---|---|
An Information Theory-Based Feature Selection Framework for Big Data Under Apache Spark |
Abstract | ||
|---|---|---|
With the advent of extremely high dimensional datasets, dimensionality reduction techniques are becoming mandatory. Of the many techniques available, feature selection (FS) is of growing interest for its ability to identify both relevant features and frequently repeated instances in huge datasets. We aim to demonstrate that standard FS methods can be parallelized in big data platforms like Apache ... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TSMC.2017.2670926 | IEEE Transactions on Systems, Man, and Cybernetics: Systems |
Keywords | DocType | Volume |
Big Data,Sparks,Feature extraction,Programming,Distributed databases,Standards,Data mining | Journal | 48 |
Issue | ISSN | Citations |
9 | 2168-2216 | 12 |
PageRank | References | Authors |
0.52 | 15 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sergio Ramírez-Gallego | 1 | 98 | 6.99 |
| Héctor Mouriño-Talín | 2 | 12 | 0.52 |
| David Martínez-Rego | 3 | 143 | 12.70 |
| Verónica Bolón-Canedo | 4 | 476 | 33.04 |
| José Manuel Benítez | 5 | 888 | 56.02 |
| Amparo Alonso-Betanzos | 6 | 885 | 76.98 |
| Francisco Herrera | 7 | 27391 | 1168.49 |