Using couple of datasets, analysis by comparing clustering algorithms between WEKA and MATLAB platforms

Nowadays, it is impossible to follow technological developments because of it's rapidly growing trend. As a result of this trend, new branches of business sectors appear. One of the sub branch of technology area which is called as database systems faced with same situation. It is effected by this technological growing trend. Data mining sector had been derivated like this way. Former database systems only cares personal and meta datas and see the other datas as a weight. But today, with the help of artifical intelligence and scientific flexible calculation ways data stacks has become more important than ever. The people who become experienced about data mining and it's usage, can use their abilities in parallel business sectors.For instance, finance sector personnels can perform their datamining skills on predicting the future of their special area. On the other hand, company can measure gladness of their customers according to social media responses. Business men can predict or estimate their current and future position in the global and local market. As a summary, expectation of the employees which includes tech workers and business specialists are using data mining solutions for prediction. And prediction job has always links with clustering algorithms. That's why I choose comparing clustering algorithms over some Boğaziçi University Kandilli Observatory and Earthquake Research Institute values of Turkey as a master thesis of mine. For accomplish this task, I used Matlab and Weka platforms as computer programmes. I choosed mostly used clustering algorithms which are K-Means, Expectation Maximization and Hierarchical Clustering algorithms to compare with each other. With the help of these comparisons, I would like to be experienced about clustering algorithms and their mostly used platforms. Firstly, I defined each algorithm on both platforms and than I opportunity to compare them with each other according to their advantages and disadvantages.