A comparison of data mining methods for prediction and classification types of quality problems

Download
2009
Anaklı, Zeynep
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 these methods are not valid for quality improvement data. Furthermore, these studies do not consider all relevant decision criteria in their comparison. All relevant criteria and interdependencies among criteria should be taken into consideration during the performance evaluation. In this study, classification DM methods namely; Decision Trees (DT), Neural Networks (NN), Multivariate Adaptive Regression Splines (MARS), Logistic Regression (LR), Mahalanobis-Taguchi System (MTS), Fuzzy Classifier (FC) and Support Vector Machine (SVM); prediction DM methods DT, NN, MARS, Multiple Linear Regression (MLR), Fuzzy Regression (FR) and Robust Regression (RR) are prioritized according to a comprehensive set of criteria using ANP and PROMETHEE. According to results of this study, MARS is found superior to the other methods for both classification and prediction. Moreover, sensitivity of the results to changes in weights and thresholds of the decision criteria is analyzed. These analyses show that resulting priorities are very insensitive to these parameters.

Suggestions

Hybrid ranking approaches based on data envelopment analysis and outranking relations
Eryılmaz, Utkan; Karasakal, Esra; Department of Industrial Engineering (2006)
In this study two different hybrid ranking approaches based on data envelopment analysis and outranking relations for ranking alternatives are proposed. Outranking relations are widely used in Multicriteria Decision Making (MCDM) for ranking the alternatives and appropriate in situations when we have limited information on the preference structure of the decision maker. Yet to apply these methods DM should provide exact values for method parameters (weights, thresholds etc.) as well as basic information suc...
R&D project performance evaluation with multiple and interdependent criteria
Tohumcu, Zeynep; Karasakal, Esra; Department of Industrial Engineering (2007)
In this study, an Analytic Network Process (ANP) and Data Envelopment Analysis (DEA) based approach was developed in order to measure the performance of customer-based Research and Development projects being executed in TÜB TAKSAGE, Defense Research and Development Institute, under the Scientific and Technological Research Council of Turkey. In order to evaluate project performance, many criteria, containing various subcriteria were determined. In order to handle the interdependencies among the criteria and...
A probabilistic approach to multi criteria sorting problem
Buğdacı, Aslı Gül; Köksalan, Murat; Department of Industrial Engineering (2009)
We aim to classify alternatives evaluated in multiple criteria among preference ordered classes assuming an underlying additive utility function. We develop a probabilistic classification method by calculating the probability of an alternative being in each class. We assign alternatives to classes based on threshold probabilities. We require the decision maker to place an alternative to a class when no alternatives satisfy the required thresholds. We find new probabilities for unassigned alternatives in the...
A comparison of some robust regression techniques
Avcı, Ezgi; Köksal, Gülser; Department of Industrial Engineering (2009)
Robust regression is a commonly required approach in industrial studies like data mining, quality control and improvement, and finance areas. Among the robust regression methods; Least Median Squares, Least Trimmed Squares, Mregression, MM-method, Least Absolute Deviations, Locally Weighted Scatter Plot Smoothing and Multivariate Adaptive Regression Splines are compared under contaminated normal distributions with each other and Ordinary Least Squares with respect to the multiple outlier detection performan...
An evaluation of the reinsepction decision policies for software code inspections
Nalbant, Serkan; Köksal, Gülser; Department of Industrial Engineering (2005)
This study evaluates a number of software reinspection decision policies for software code inspections with the aim of revealing their effects regarding cost, schedule and quality related objectives of a software project. Software inspection is an effective defect removal technique for software projects. After the initial inspection, a reinspection may be performed for decreasing the number of remaining defects further. Although, various reinspection decision methods are proposed in the literature, no study...
Citation Formats
Z. Anaklı, “A comparison of data mining methods for prediction and classification types of quality problems,” M.S. - Master of Science, Middle East Technical University, 2009.