Abstract
In this paper, a framework for replacing missing values in a database is proposed since a real-world database is seldom complete. Good data quality in a database can directly improve the performance of any data mining algorithm in various applications. Our proposed framework adopts the basic concepts from conditional probability theories and further develops an algorithm to facilitate the capability of handling both nominal and numerical values, which addresses the problem of the inability of handling both nominal and numerical values with a high degree of accuracy in the existing algorithms. Several experiments are conducted and the experimental results demonstrate that our framework provides a high accuracy when compared with most of the commonly used algorithms such as using the average value, using the maximum value, and using the minimum value to replace missing values.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 2005 IEEE International Conference on Information Reuse and Integration, IRI - 2005 |
| Pages | 199-204 |
| Number of pages | 6 |
| Volume | 2005 |
| DOIs | |
| State | Published - Dec 1 2005 |
| Event | 2005 IEEE International Conference on Information Reuse and Integration, IRI - 2005 - Las Vegas, NV, United States Duration: Aug 15 2005 → Aug 17 2005 |
Other
| Other | 2005 IEEE International Conference on Information Reuse and Integration, IRI - 2005 |
|---|---|
| Country | United States |
| City | Las Vegas, NV |
| Period | 8/15/05 → 8/17/05 |
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ASJC Scopus subject areas
- Engineering(all)
Cite this
Handling missing values via decomposition of the conditioned set. / Shyu, Mei-Ling; Kuruppu-Appuhamilage, Indika Priyantha; Chen, Shu Ching; Chang, Li Wu.
Proceedings of the 2005 IEEE International Conference on Information Reuse and Integration, IRI - 2005. Vol. 2005 2005. p. 199-204 1506473.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Handling missing values via decomposition of the conditioned set
AU - Shyu, Mei-Ling
AU - Kuruppu-Appuhamilage, Indika Priyantha
AU - Chen, Shu Ching
AU - Chang, Li Wu
PY - 2005/12/1
Y1 - 2005/12/1
N2 - In this paper, a framework for replacing missing values in a database is proposed since a real-world database is seldom complete. Good data quality in a database can directly improve the performance of any data mining algorithm in various applications. Our proposed framework adopts the basic concepts from conditional probability theories and further develops an algorithm to facilitate the capability of handling both nominal and numerical values, which addresses the problem of the inability of handling both nominal and numerical values with a high degree of accuracy in the existing algorithms. Several experiments are conducted and the experimental results demonstrate that our framework provides a high accuracy when compared with most of the commonly used algorithms such as using the average value, using the maximum value, and using the minimum value to replace missing values.
AB - In this paper, a framework for replacing missing values in a database is proposed since a real-world database is seldom complete. Good data quality in a database can directly improve the performance of any data mining algorithm in various applications. Our proposed framework adopts the basic concepts from conditional probability theories and further develops an algorithm to facilitate the capability of handling both nominal and numerical values, which addresses the problem of the inability of handling both nominal and numerical values with a high degree of accuracy in the existing algorithms. Several experiments are conducted and the experimental results demonstrate that our framework provides a high accuracy when compared with most of the commonly used algorithms such as using the average value, using the maximum value, and using the minimum value to replace missing values.
UR - http://www.scopus.com/inward/record.url?scp=33745697521&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33745697521&partnerID=8YFLogxK
U2 - 10.1109/IRI-05.2005.1506473
DO - 10.1109/IRI-05.2005.1506473
M3 - Conference contribution
AN - SCOPUS:33745697521
SN - 0780390938
SN - 9780780390935
VL - 2005
SP - 199
EP - 204
BT - Proceedings of the 2005 IEEE International Conference on Information Reuse and Integration, IRI - 2005
ER -