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**1 - 3**of**3**### BRITAIN’S CHANGING REGIONAL GEOGRAPHY

, 2009

"... Family names as indicators of Britain’s changing regional geography ISSN 1467-1298 ..."

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Family names as indicators of Britain’s changing regional geography ISSN 1467-1298

### Review of Existing Methods for Finding Initial Clusters in K-means Algorithm

"... Clustering is one of the Data Mining tasks that can be used to cluster or group objects on the basis of their nearness to the central value. It has found many applications in the field of business, image processing, medical etc. K Means is one the method of clustering which is used widely because it ..."

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Clustering is one of the Data Mining tasks that can be used to cluster or group objects on the basis of their nearness to the central value. It has found many applications in the field of business, image processing, medical etc. K Means is one the method of clustering which is used widely because it is simple and efficient. The output of the K Means depends upon the chosen central values for clustering. So accuracy of the K Means algorithm depends much on the chosen central values. This paper presents the various methods evolved by researchers for finding initial clusters for K Means.

### MINING ON CAR DATABASE EMPLOYING LEARNING AND CLUSTERING ALGORITHMS

"... Abstract—In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the known learning algorithms used are Naïve Bayesian (NB) and SMO (Self-Minimal-Optimisation).Thus the following two learning algorithms are used on a Car ..."

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Abstract—In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the known learning algorithms used are Naïve Bayesian (NB) and SMO (Self-Minimal-Optimisation).Thus the following two learning algorithms are used on a Car review database and thus a model is hence created which predicts the characteristic of a review comment after getting trained. It was found that model successfully predicted correctly about the review comments after getting trained. Also two clustering algorithms: K-Means and Self Organising Maps (SOM) are used and worked upon a Car Database (which contains the properties of many different CARS), and thus the following two results are then compared. It was found that K-Means algorithm formed better clusters on the same data set. Keyword-Data Mining, Naïve Bayesian, SMO, K-Mean, SOM, Car review database I.