期刊論文
| 學年 | 99 |
|---|---|
| 學期 | 2 |
| 出版（發表）日期 | 2011-03-01 |
| 作品名稱 | KNN-DTW Based Missing Value Imputation for Microarray Time Series Data |
| 作品名稱（其他語言） | |
| 著者 | Hsu, Hui-Huang; Yang, Andy C.; Lu, Ming-Da |
| 單位 | 淡江大學資訊工程學系 |
| 出版者 | Oulu: Academy Publisher |
| 著錄名稱、卷期、頁數 | Journal of Computers 6(3), pp.418-425 |
| 摘要 | Microarray technology provides an opportunity for scientists to analyze thousands of gene expression profiles simultaneously. However, microarray gene expression data often contain multiple missing expression values due to many reasons. Effective methods for missing value imputation in gene expression data are needed since many algorithms for gene analysis require a complete matrix of gene array values. Several algorithms are proposed to handle this problem, but they have various limitations. In this paper, we develop a novel method to impute missing values in microarray time-series data combining k-nearest neighbor (KNN) and dynamic time warping (DTW). We also analyze and implement several variants of DTW to further improve the efficiency and accuracy of our method. Experimental results show that our method is more accurate compared with existing missing value imputation methods on real microarray time series datasets. |
| 關鍵字 | Microarray Time Series Data;Missing Value Imputation;Dynamic Time Warping;K-Nearest Neighbor |
| 語言 | en |
| ISSN | 1796-203X |
| 期刊性質 | 國外 |
| 收錄於 | EI |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | 否 |
| 國別 | FIN |
| 公開徵稿 | |
| 出版型式 | ,紙本 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/55114 ) |