CAR EVALUATION METHODOLOGY USING REGRESSION MODELS

• Main Authors: AQUEEL AZHAR, 安志瀚
• Other Authors: CHEN,YEN-LUN
• Format: Others
• Language: en_US
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/tq5zr6

碩士 === 國立高雄師範大學 === 工程國際碩士學位學程 === 106 === Taking a good decision for acquiring an automobile and understand its concept is very much an important aspect of buying an automobile especially for those who are naïve and has no experience in how the automobile industry works. There are many facets which can influence the decision of buying a car for an individual with some of his/her desires. Influencing factors mainly the prize, the regular maintenance, comfort, and safety are few crucial and possible problem arising factors that needed to be considered. Car evaluation database is very important structural information that someone should look at for the features and classification of each car could be helpful in our decision making. Because of its underlying concept structure, this database is very informative particularly useful for testing practical training and structure discovery methods. This database classifies cars specifications according to PRICE, COMFORT, and SAFETY. In the 1990’s, DEX contributed to solution of complex decision making problems in industry, health-care, project evaluation, housing, and sports. They are also important for the analysis, simulation and explanation of options. Decision trees have several advantages over traditional supervised classification procedures used in remote sensing such as maximum likelihood classification. Decision models are typically developed by decaying or dividing of the complex problem of decision into small and less mosaic problems with small units of problems; the result of such decomposition is a hierarchical structure that consists of attributes and utility functions Car Evaluation Database was derived from a simple hierarchical decision model originally developed for the demonstration of Decision Expert (DEX).