In the case of classification the objects of a

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Unformatted text preview: r patterns extracted as the result of data mining are a new knowledge obtained which was previously unknown in the organization (hidden in the organization's data). 4. Potentially useful information. This means that the information extracted as the result of data mining is valuable and useful for the intended user or task (for better decision support). For being useful, it should also be understandable (if not immediately, then after some post processing). Classification of Data Mining Algorithms Many types of patterns normally exist in a large database. Different types of algorithms are needed to extract different kinds of patterns. Some of the most popular classes of algorithms used for data mining are: 1. Classification, 2. Clustering, 3. Association, and 4. Trend analysis They are briefly described below. Classification The objective of classification algorithms for data mining is to classify the objects of a database into one of several predefined categorical classes. A classification algorithm is designed to determine the class of an object based on its attributes. In this method, a set of objects is first taken as the training set, and every object in this set is represented by a vector of attributes along with its class. Then a classification function or model is constructed by analyzing the relationship between the attributes and the classes of the objects in the training set. This classification function or model is then applied to all objects in a database to classify them into the already defined classes. This helps the user in having a better understanding of the classes of the objects in the database. A simple application of classification algorithm may be to classify the patient records of a patient database into different classes of diseases. The personal and clinical data of a patient's record may be used as the attributes for classification. The classified information may be used by the hospital management personnel to make decisions regarding, how many doctors and other staff should be employed with certain speciality and skil...
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This document was uploaded on 04/07/2014.

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