Name
Title | ||
|---|---|---|
ROSEFW-RF: The winner algorithm for the ECBDL’14 big data competition: An extremely imbalanced big data bioinformatics problem |
Abstract | ||
|---|---|---|
The application of data mining and machine learning techniques to biological and biomedicine data continues to be an ubiquitous research theme in current bioinformatics. The rapid advances in biotechnology are allowing us to obtain and store large quantities of data about cells, proteins, genes, etc., that should be processed. Moreover, in many of these problems such as contact map prediction, the problem tackled in this paper, it is difficult to collect representative positive examples. Learning under these circumstances, known as imbalanced big data classification, may not be straightforward for most of the standard machine learning methods. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1016/j.knosys.2015.05.027 | Knowledge-Based Systems |
Keywords | DocType | Volume |
Bioinformatics,Big data,Hadoop,MapReduce,Imbalance classification,Evolutionary feature selection | Journal | 87 |
ISSN | Citations | PageRank |
0950-7051 | 9 | 0.50 |
References | Authors | |
27 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Isaac Triguero | 1 | 633 | 31.76 |
| S. del Río | 2 | 243 | 8.92 |
| Victoria López | 3 | 765 | 20.95 |
| Jaume Bacardit | 4 | 1091 | 47.21 |
| José Manuel Benítez | 5 | 888 | 56.02 |
| Francisco Herrera | 6 | 27391 | 1168.49 |