An improved organization method for association rules and a basis for comparison of methods

Download

index.pdf

Date

2010

Author

Jabarnejad, Masood

Metadata

Show full item record

Item Usage Stats

177
views

53
downloads

In large data, set of mined association rules are typically large in number and hard to interpret. Some grouping and pruning methods have been developed to make rules more understandable. In this study, one of these methods is modified to be more effective and more efficient in applications including low thresholds for support or confidence, such as association analysis of product/process quality improvement. Results of experiments on benchmark datasets show that the proposed method groups and prunes more rules. In the literature, many rule reduction methods, including grouping and pruning methods, have been proposed for different applications. The variety in methods makes it hard to select the right method for applications such those of quality improvement. In this study a novel performance comparison basis is introduced to address this problem. It is applied here to compare the improved method to the original one. The introduced basis is tailored for quality data, but is flexible and can be changed to be applicable in other application domains.

Subject Keywords

Industrial engineering.

URI

http://etd.lib.metu.edu.tr/upload/12611960/index.pdf
https://hdl.handle.net/11511/19604

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

The general lot sizing and scheduling problem with sequence dependent changeovers Koçlar, Ayşe; Süral, Haldun; Department of Industrial Engineering (2005) In this study, we consider the General Lot Sizing and Scheduling Problem in single level capacitated environments with sequence dependent item changeovers. Process industries may be regarded as suitable application areas of the problem. The focus on capacity utilization and intensively time consuming changeovers necessitate the integration of lot sizing and sequencing decisions in the production plan. We present a mathematical model which captures the essence of cases in the most generic and realistic setti...
Fuzzy classification models based on tanaka’s fuzzy linear regression approach and nonparametric improved fuzzy classifier functions Özer, Gizem; Köksal, Gülser; Department of Industrial Engineering (2009) In some classification problems where human judgments, qualitative and imprecise data exist, uncertainty comes from fuzziness rather than randomness. Limited number of fuzzy classification approaches is available for use for these classification problems to capture the effect of fuzzy uncertainty imbedded in data. The scope of this study mainly comprises two parts: new fuzzy classification approaches based on Tanaka’s Fuzzy Linear Regression (FLR) approach, and an improvement of an existing one, Improved Fu...
A comparison of data mining methods for prediction and classification types of quality problems Anaklı, Zeynep; Anaklı, Zeynep; Department of Industrial Engineering (2009) In this study, an Analytic Network Process (ANP) and Preference Ranking Organization MeTHod for Enrichment Evaluations (PROMETHEE) based approach is developed and used to compare overall performance of some commonly used classification and prediction data mining methods on quality improvement data, according to several decision criteria. Classification and prediction data mining (DM) methods are frequently used in many areas including quality improvement. Previous studies on comparison of performance of the...
Monitoring high quality processes: a study of estimation errors on the time-between-events exponentially weighted moving average schemes Özsan, Güney; Köksal, Gülser; Department of Industrial Engineering (2008) In some production environments the defect rates are considerably low such that measurement of fraction of nonconforming items reaches parts per million level. In such environments, monitoring the number of conforming items between consecutive nonconforming items, namely the time between events (TBE) is often suggested. However, in the design of control charts for TBE monitoring a common practice is the assumptions of known process parameters. Nevertheless, in many applications the true values of the proces...
Multi-class classification methods utilizing mahalanobis taguchi system and a re-sampling approach for imbalanced data sets Ayhan, Dilber; Köksal, Gülser; Department of Industrial Engineering (2009) Classification approaches are used in many areas in order to identify or estimate classes, which different observations belong to. The classification approach, Mahalanobis Taguchi System (MTS) is analyzed and further improved for multi-class classification problems under the scope of this thesis study. MTS tries to explore significant variables and classify a new observation based on its Mahalanobis distance (MD). In this study, first, sample size problems, which are encountered mostly in small data sets, a...

Citation Formats

M. Jabarnejad, “An improved organization method for association rules and a basis for comparison of methods,” M.S. - Master of Science, Middle East Technical University, 2010.