Name
Title | ||
|---|---|---|
A robust correlation analysis framework for imbalanced and dichotomous data with uncertainty. |
Abstract | ||
|---|---|---|
•The Pearson correlation coefficient deviation with data imbalanced is studied.•RCAF is proposed to minimize correlation coefficient deviation for imbalanced data.•SMOTE and ADASYN are compared for correlation analysis.•Correlation between weather conditions and clearness index is explored. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.ins.2018.08.017 | Information Sciences |
Keywords | Field | DocType |
Pearson product-moment correlation,Imbalanced data,Clearness index,Dichotomous variable | Correlation coefficient,Pearson product-moment correlation coefficient,Correlation,Sampling (statistics),Artificial intelligence,Solar irradiance,Statistics,Standard deviation,Correlation analysis,Machine learning,Weather condition,Mathematics | Journal |
Volume | ISSN | Citations |
470 | 0020-0255 | 2 |
PageRank | References | Authors |
0.64 | 31 | 10 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chun Sing Lai | 1 | 41 | 15.62 |
| Yingshan Tao | 2 | 2 | 0.64 |
| Fangyuan Xu | 3 | 2 | 1.65 |
| Wing W. Y. Ng | 4 | 528 | 56.12 |
| Youwei Jia | 5 | 72 | 8.28 |
| H. Yuan | 6 | 184 | 25.59 |
| Chao Huang | 7 | 3 | 1.67 |
| Loi Lei Lai | 8 | 135 | 38.72 |
| Zhou Xu | 9 | 66 | 15.44 |
| Giorgio Locatelli | 10 | 4 | 1.35 |