Data Mining Algorithms for Classification

In: Computers and Technology

Submitted By aprajita3
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Data Mining Algorithms for Classification
BSc Thesis Artificial Intelligence Author: Patrick Ozer Radboud University Nijmegen January 2008

Supervisor: Dr. I.G. Sprinkhuizen-Kuyper Radboud University Nijmegen

Abstract Data Mining is a technique used in various domains to give meaning to the available data. In classification tree modeling the data is classified to make predictions about new data. Using old data to predict new data has the danger of being too fitted on the old data. But that problem can be solved by pruning methods which degeneralizes the modeled tree. This paper describes the use of classification trees and shows two methods of pruning them. An experiment has been set up using different kinds of classification tree algorithms with different pruning methods to test the performance of the algorithms and pruning methods. This paper also analyzes data set properties to find relations between them and the classification algorithms and pruning methods.

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Introduction

The last few years Data Mining has become more and more popular. Together with the information age, the digital revolution made it necessary to use some heuristics to be able to analyze the large amount of data that has become available. Data Mining has especially become popular in the fields of forensic science, fraud analysis and healthcare, for it reduces costs in time and money. One of the definitions of Data Mining is; “Data Mining is a process that consists of applying data analysis and discovery algorithms that, under acceptable computational efficiency limitations, produce a particular enumeration of patterns (or models) over the data” [4]. Another , sort of pseudo definition; “The induction of understandable models and patterns from databases” [6]. In other words, we initially have a large (possibly infinite) collection of possible models (patterns) and (finite) data. Data Mining…...

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