A modified K-means algorithm for clustering data sets with missing values using adaptive imputation / (Record no. 467)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02531nam a2200241 4500 |
| 001 - CONTROL NUMBER | |
| control field | UPMIN-00000010164 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | UPMIN |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20230201170740.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 230201b |||||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | DLC |
| Transcribing agency | UPMin |
| Modifying agency | upmin |
| 041 ## - LANGUAGE CODE | |
| Language code of text/sound track or separate title | eng |
| 090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) | |
| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) | LG993.5 2005 |
| Local cutter number (OCLC) ; Book number/undivided call number, CALL (RLIN) | A64 M35 |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Mamalias, Lovella V. |
| 9 (RLIN) | 2024 |
| 245 00 - TITLE STATEMENT | |
| Title | A modified K-means algorithm for clustering data sets with missing values using adaptive imputation / |
| Statement of responsibility, etc. | Lovella V. Mamalias |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Date of publication, distribution, etc. | 2005 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 64 leaves |
| 502 ## - DISSERTATION NOTE | |
| Dissertation note | Thesis (BS Applied Mathematics) -- University of the Philippines Mindanao, 2005 |
| 520 3# - SUMMARY, ETC. | |
| Summary, etc. | Clustering is a technique for partitioning the complete data set into groups such that data points belonging to the same group are more similar than the data points in other groups. However, missing data is common in data sets. Clustering data set with missing values are usually done by deleting the missing data and cluster only the remaining complete data points. Another approach is done by filling-up first the missing values before the clustering stage using the information from the complete data points making the incomplete data set a complete data set. However, these methods might jeopardize the quality of the clustering result. This study deals with clustering data set with missing values that uses imputation during the clustering stage. The k-means clustering method was modified such that incomplete data set can be partitioned into groups. The distance function was modified so that membership of the incomplete data points to the nearest cluster can be obtained. The computation for the new cluster center was also modified so that a new cluster center can be obtained from the data points (including the incomplete data points) belonging on the same cluster. The performance of the modified k-means algorithm was compared with the performance of the two other clustering methods that deal with missing values namely, k-means after case deletion and k-means after mean imputation. Modified k-means, although less efficient, has better quality of clustering result in terms of cluster recovery when compared with the other clustering methods. The modified k-means algorithm was applied to the Philippine eagle data, an incomplete data having missing values. The clustering result of the proposed algorithm was compared with the clustering result using k-means after attribute deletion. |
| 658 ## - INDEX TERM--CURRICULUM OBJECTIVE | |
| Main curriculum objective | Undergraduate Thesis |
| Curriculum code | AMAT200 |
| 905 ## - LOCAL DATA ELEMENT E, LDE (RLIN) | |
| a | Fi |
| 905 ## - LOCAL DATA ELEMENT E, LDE (RLIN) | |
| a | UP |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Library of Congress Classification |
| Koha item type | Thesis |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Status | Collection | Home library | Current library | Shelving location | Date acquired | Source of acquisition | Accession Number | Total Checkouts | Full call number | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Library of Congress Classification | Not For Loan | Preservation Copy | University Library | University Library | Archives and Records | 2005-07-05 | donation | UAR-T-gd592 | LG993.5 2005 A64 M35 | 3UPML00022035 | 2022-09-21 | 2022-09-21 | Thesis | ||||
| Library of Congress Classification | Not For Loan | Room-Use Only | College of Science and Mathematics | University Library | Theses | 2005-05-24 | donation | CSM-T-gd1236 | LG993.5 2005 A64 M35 | 3UPML00011332 | 2022-09-21 | 2022-09-21 | Thesis |