Name
Abstract | ||
|---|---|---|
•Comparison of distance functions that handle missing data across 61 public datasets.•Study of SIMDIST and MDE for imputation and extension of MDE for the nominal case.•Exploration of understudied HEOM and HVDM redefinitions.•Distance metrics affect KNN imputation, especially for higher missing rates.•Differences in performance between distances rely on their treatment of missing values. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.patrec.2020.05.032 | Pattern Recognition Letters |
Keywords | DocType | Volume |
Missing Data,Data Imputation,k-nearest neighbours,Distance Functions,Heterogeneous Data,Imbalanced Data | Journal | 136 |
ISSN | Citations | PageRank |
0167-8655 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Miriam Seoane Santos | 1 | 31 | 5.28 |
| Pedro Abreu | 2 | 92 | 19.58 |
| Szymon Wilk | 3 | 461 | 40.94 |
| Jo ão M. Santos | 4 | 10 | 6.95 |