Ekonomik Verilerin Spektral Kümeleme

In this thesis were implemented two of the most important algorithms in the data mining spectral clustering and k_mean ,tring to find the variances between them where the study was conducted on the statistics and studies from data warehouse EEA (European Economic Association) in thirty-one countries in the European Union in the seven years from 2008 to 2013, which was The first study classifies the People at risk of poverty or social exclusion, while the second one is Population tertiary by education attainment level And the last is Mean and median income by work intensity of the household. In the first phase has been calibrated and format of the data in order to apply the algorithm, it has also been making some adjustments and guess some of the lost values of statistics according to the laws of statistics, The second stage, so we execute the algorithm program which wrote in matlap language version no14, then the results represented in 3D Finally, all the results analyzed, therefore the benefits and advantages, Find the relationship between three factors and which one effect to other than clustering the thirty-one countries with a year of studies in three different clusters. In rich countries where people have well-being life and high living rate, The percentage for risk of poverty decreases and we noted rising the percentage of high educational attainment, because people in those countries have Comfort and stability life ,While in the least well-being countries, we note rise the number of people at risk of poverty and decrease percentage educational attainment, so these people be more deal with reality and Approaching to the obsessions and fears of the future, so they try to be Self-reliance by, As a result, turning the labor market for attend to find a job opportunity at early age.