MARC details
| 000 -LEADER |
|---|
| fixed length control field |
01789nam a22003133a 4500 |
| 001 - CONTROL NUMBER |
|---|
| control field |
UPMIN-00003211628 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
UPMIN |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20230202144919.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
230202b |||||||| |||| 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 #0 - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) |
|---|
| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) |
LG993.5 2008 |
| Local cutter number (OCLC) ; Book number/undivided call number, CALL (RLIN) |
A64 M37 |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Marbas, Ivan Art F. |
| 9 (RLIN) |
2070 |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
Clustering datasets with missing values using modified K-medoids algorithm / |
| Statement of responsibility, etc. |
Ivan Art F. Marbas. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Date of publication, distribution, etc. |
2008 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
61 leaves. |
| 502 ## - DISSERTATION NOTE |
|---|
| Dissertation note |
Thesis (BS Applied Mathematics) -- University of the Philippines Mindanao, 2008 |
| 520 3# - SUMMARY, ETC. |
|---|
| Summary, etc. |
A modification was done to the Euclidean distance to compute distance for incomplete data points, at the same time flagging them so that the algorithm will avoid choosing them as cluster medoids. This resulted to the Modified K-medoids clustering algorithm applied with pre-processing methods, namely, Case Deletion, Mean Imputation and K-nearest Neighbor Imputation, in clustering incomplete datasets, it showed that the proposed algorithm performs only second best to K-nearest Neighbor Imputation. The comparison was made using incomplete datasets generated from the Iris and Bupa dataset with different missing value occurrences and degradation levels. Though only second best, the production of cluster medoids with no missing values is unique to the modification. Thus, the Modified K-medoids clustering algorithm is more advantageous. |
| 650 17 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Clustering. |
| 9 (RLIN) |
366 |
| 650 17 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Incomplete datasets. |
| 9 (RLIN) |
2071 |
| 650 17 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
K-medoids. |
| 9 (RLIN) |
2072 |
| 650 17 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Modified Euclidiean distance. |
| 9 (RLIN) |
2073 |
| 650 17 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Datasets. |
| 9 (RLIN) |
1958 |
| 650 17 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Euclidean distance. |
| 9 (RLIN) |
2074 |
| 658 ## - INDEX TERM--CURRICULUM OBJECTIVE |
|---|
| Main curriculum objective |
Undergraduate Thesis |
| Curriculum code |
AMAT200, |
| Source of term or code |
BSAM |
| 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 |
