A relative tolerance relation of rough set with reduct and core approach, and application to incomplete information systems
Data mining concepts and methods can be applied in various fields. Many methods have been proposed and one of those methods is the classical 'rough set theory' which is used to analyze the complete data. However, the Rough Set classical theory cannot overcome the incomplete data. The si...
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English English English |
| Published: |
2020
|
| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/4936/1/24p%20RD.%20ROHMAT%20SAEDUDIN.pdf http://eprints.uthm.edu.my/4936/2/RD.%20ROHMAT%20SAEDUDIN%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/4936/3/RD.%20ROHMAT%20SAEDUDIN%20WATERMARK.pdf |
| _version_ | 1825709934623326208 |
|---|---|
| author | Saedudin, Rd. Rohmat |
| author_facet | Saedudin, Rd. Rohmat |
| author_sort | Saedudin, Rd. Rohmat |
| collection | UTHM |
| description | Data mining concepts and methods can be applied in various fields. Many methods
have been proposed and one of those methods is the classical 'rough set theory' which
is used to analyze the complete data. However, the Rough Set classical theory cannot
overcome the incomplete data. The simplest method for operating an incomplete data
is removing unknown objects. Besides, the continuation of Rough Set theory is called
tolerance relation which is less convincing decision in terms of approximation. As a
result, a similarity relation is proposed to improve the results obtained through a
tolerance relation technique. However, when applying the similarity relation, little
information will be lost. Therefore, a limited tolerance relation has been introduced.
However, little information will also be lost as limited tolerance relation does not take
into account the accuracy of the similarity between the two objects. Hence, this study
proposed a new method called Relative Tolerance Relation of Rough Set with Reduct
and Core (RTRS) which is based on limited tolerance relation that takes into account
relative similarity precision between two objects. Several incomplete datasets have
been used for data classification and comparison of our approach with existing baseline
approaches, such as the Tolerance Relation, Limited Tolerance Relation, and NonSymmetric
Similarity
Relations
approaches
are
made
based
on
two
different
scenarios.
In
the
first
scenario,
the
datasets
are
given
the
same
weighting
for all
attributes.
In the
second
scenario,
each
attribute
is
given
a
different
weighting.
Once
the
classification
process
is complete, the proposed approach will eliminate redundant attributes to
develop an efficient reduce set and formulate the basic attribute specified in the
incomplete information system. Several datasets have been tested and the rules
generated from the proposes approach give better accuracy. Generally, the findings
show that the RTRS method is better compared to the other methods as discussed in
this study. |
| first_indexed | 2024-03-05T21:49:56Z |
| format | Thesis |
| id | uthm.eprints-4936 |
| institution | Universiti Tun Hussein Onn Malaysia |
| language | English English English |
| last_indexed | 2024-03-05T21:49:56Z |
| publishDate | 2020 |
| record_format | dspace |
| spelling | uthm.eprints-49362022-02-03T03:16:13Z http://eprints.uthm.edu.my/4936/ A relative tolerance relation of rough set with reduct and core approach, and application to incomplete information systems Saedudin, Rd. Rohmat T Technology (General) QA71-90 Instruments and machines Data mining concepts and methods can be applied in various fields. Many methods have been proposed and one of those methods is the classical 'rough set theory' which is used to analyze the complete data. However, the Rough Set classical theory cannot overcome the incomplete data. The simplest method for operating an incomplete data is removing unknown objects. Besides, the continuation of Rough Set theory is called tolerance relation which is less convincing decision in terms of approximation. As a result, a similarity relation is proposed to improve the results obtained through a tolerance relation technique. However, when applying the similarity relation, little information will be lost. Therefore, a limited tolerance relation has been introduced. However, little information will also be lost as limited tolerance relation does not take into account the accuracy of the similarity between the two objects. Hence, this study proposed a new method called Relative Tolerance Relation of Rough Set with Reduct and Core (RTRS) which is based on limited tolerance relation that takes into account relative similarity precision between two objects. Several incomplete datasets have been used for data classification and comparison of our approach with existing baseline approaches, such as the Tolerance Relation, Limited Tolerance Relation, and NonSymmetric Similarity Relations approaches are made based on two different scenarios. In the first scenario, the datasets are given the same weighting for all attributes. In the second scenario, each attribute is given a different weighting. Once the classification process is complete, the proposed approach will eliminate redundant attributes to develop an efficient reduce set and formulate the basic attribute specified in the incomplete information system. Several datasets have been tested and the rules generated from the proposes approach give better accuracy. Generally, the findings show that the RTRS method is better compared to the other methods as discussed in this study. 2020-10 Thesis NonPeerReviewed text en http://eprints.uthm.edu.my/4936/1/24p%20RD.%20ROHMAT%20SAEDUDIN.pdf text en http://eprints.uthm.edu.my/4936/2/RD.%20ROHMAT%20SAEDUDIN%20COPYRIGHT%20DECLARATION.pdf text en http://eprints.uthm.edu.my/4936/3/RD.%20ROHMAT%20SAEDUDIN%20WATERMARK.pdf Saedudin, Rd. Rohmat (2020) A relative tolerance relation of rough set with reduct and core approach, and application to incomplete information systems. Doctoral thesis, Universiti Tun Hussein Malaysia. |
| spellingShingle | T Technology (General) QA71-90 Instruments and machines Saedudin, Rd. Rohmat A relative tolerance relation of rough set with reduct and core approach, and application to incomplete information systems |
| title | A relative tolerance relation of rough set with reduct and core approach, and application to incomplete information systems |
| title_full | A relative tolerance relation of rough set with reduct and core approach, and application to incomplete information systems |
| title_fullStr | A relative tolerance relation of rough set with reduct and core approach, and application to incomplete information systems |
| title_full_unstemmed | A relative tolerance relation of rough set with reduct and core approach, and application to incomplete information systems |
| title_short | A relative tolerance relation of rough set with reduct and core approach, and application to incomplete information systems |
| title_sort | relative tolerance relation of rough set with reduct and core approach and application to incomplete information systems |
| topic | T Technology (General) QA71-90 Instruments and machines |
| url | http://eprints.uthm.edu.my/4936/1/24p%20RD.%20ROHMAT%20SAEDUDIN.pdf http://eprints.uthm.edu.my/4936/2/RD.%20ROHMAT%20SAEDUDIN%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/4936/3/RD.%20ROHMAT%20SAEDUDIN%20WATERMARK.pdf |
| work_keys_str_mv | AT saedudinrdrohmat arelativetolerancerelationofroughsetwithreductandcoreapproachandapplicationtoincompleteinformationsystems AT saedudinrdrohmat relativetolerancerelationofroughsetwithreductandcoreapproachandapplicationtoincompleteinformationsystems |