• The KIPS Transactions:PartD
• /
• v.8D no.3
• /
• pp.203-210
• /
• 2001

These days data is being collected and accumulated in a wide variety of fields. Stored data itself is to be an information system which helps us to make decisions. An information system includes many kinds of necessary and unnecessary attribute. So many algorithms have been developed for finding useful patterns from the data and reasoning approximately new objects. We are interested in the simple and understandable rules that can represent useful patterns. In this paper we propose an algorithm which can reduce the information in the system to a minimum, based on a probabilistic rough set theory. The proposed algorithm uses a value that tolerates accuracy of classification. The tolerant value helps minimizing the necessary attribute which is needed to reason a new object by reducing conditional attributes. It has the advantage that it reduces the time of generalizing rules. We experiment a proposed algorithm with the IRIS data and Wisconsin Breast Cancer data. The experiment results show that this algorithm retrieves a small reduct, and minimizes the size of the rule under the tolerant classification rate.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.6
• /
• pp.135-142
• /
• 2009

Data mining is an emerging area of computational intelligence that offers new theories, techniques, and tools for analysis of large data sets. The major techniques used in data mining are mining association rules, classification and clustering. Since these techniques are used individually, it is necessary to develop the methodology for rule extraction using a process of integrating these techniques. Rule extraction techniques assist humans in analyzing of large data sets and to turn the meaningful information contained in the data sets into successful decision making. This paper proposes an autonomous method of rule extraction using clustering and rough set theory. The experiments are carried out on data sets of UCI KDD archive and present decision rules from the proposed method. These rules can be successfully used for making decisions.

• Korean Journal of Heritage: History & Science
• /
• v.48 no.4
• /
• pp.110-125
• /
• 2015

This study is objected to investigate the repairing method and the modification period of rafters via the transformation traces left in the superciliums, where repair process takes places frequently. This is the basic research of analyzing the architectural features of Deokkeori, one of the additional-rafter methods. Deokkeori method can be described as using Deokdori in the top section of Hayeon, and placement of Sangyeon above it. This method was started to be used since middle of the Joseon dynasty period(middle 18th Century) and mainly used at 19th Century to resist the transformation caused by repairing. It had been gradually developed from non-application stage to application stage including additional usage of complement. The architectural features of Deokkeori can be categorized into four. First, the usage of Deokdori to connect Sangyeon to the top section of Hayeon. It reduct the direct connection between Sangyoen and Hayeon, therefore give constructive benefits and prevent the downfall of the eaves by increasing the power which pressing the top section of Hayeon. Second, it gives the autonomy to the inside structure of ceiling by comprising it. By using Deokdori, the limit of top section's longitude was eliminated while also simplify the upper section by blocking the inside structures with ceiling. In addition, the complements occasionally seen in several buildings increase the power which pressing Hayeon. Third, the ceiling's slope has been changed to be concerned with Sangyeon, instead of Hayeon which was highly related with it before. The last factor is the thickness of rafters which used in Deokkeori. The diameter is thiner in Sangyeon than Hayeon.