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DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH

LUONG, TRUNG TUAN (2005) DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH. Universiti Teknologi Petronas. (Unpublished)

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Abstract

Knowledge Discovery in Database and Data Mining use techniques derived from machine learning, visualization and statistics to investigate real world data. Their aim is to discover patterns within the data which are new, statistically valid, interesting and understandable. In recent years, there has been an explosion in computation and information technology. With it have come vast amounts of data. Lying hidden in all this data is potentially useful information that is rarely made explicit or taken advantage. New tools based both on clever applications of established algorithms and on new methodologies, empower us to do entirely new things. In this context, data mining has arisen as an important research area that helps to reveal the hidden interesting information from the rawdatacollected. The project demonstrates how data mining can address the need of business intelligence in the process of decision making. An analysis on the field of data mining is done to show how data mining can help in business such as marketing, credit card approval. The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. The proposed algorithm is a hybrid system which applied fuzzy logic and artificial neural network, which applies fuzzy logic inference to generate a set of fuzzy weighted production rules and applies artificial neural network to train the weights of fuzzy weighted rules for better classification results. Theresult of this system using the iris dataset and credit card approval dataset to evaluate the proposed algorithm's accuracy, interpretability. The project has achieved the target objectives; it can gain high accuracy for data classification task, generate rules which can help to interpret the output results, reduce the training processing. But the proposed algorithm still require high computation, the processing time will be long if the dataset is huge. However the proposed algorithm offers a promising approach to building intelligent systems.

Item Type: Final Year Project
Academic Subject : Academic Department - Information Communication Technology
Subject: Z Bibliography. Library Science. Information Resources > ZA Information resources
Divisions: Sciences and Information Technology
Depositing User: Users 2053 not found.
Date Deposited: 30 Sep 2013 16:55
Last Modified: 25 Jan 2017 09:46
URI: http://utpedia.utp.edu.my/id/eprint/7616

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