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Using K-nearest neighbor (Knn) to determine influencing factors on the national poverty line | ||
| journal of kirkuk University For Administrative and Economic Sciences | ||
| Volume 8, Issue 2, August 2018, Pages 572-589 PDF (892.92 K) | ||
| Authors | ||
| Jasim Al-Faris; Nima Abdulla AL-Fakhry | ||
| University of Kirkuk Journal For Administrative and Economic Science | ||
| Abstract | ||
| With over time the technical increases of sophistication devices and computer systems as well as networks of the Internet and Intranet, and the government institutions and non-governmental organizations became in an urgent need to shift to the information age and large databases, so it was starting to find an advanced methods such as artificial intelligence techniques. Data mining techniques are one of artificial intelligence techniques evolving to start using it's techniques and tools to extract knowledge from hideaways and reduce errors and save time.The research identify some factors affecting the national poverty line in Iraq and ways to address them by taking the advantage of wide possibilities of data mining techniques. The theoretical side of this research talking about concept of data mining and tools, as well as explaining the classifier K-nearest neighbor )Knn) and clarify the concept of poverty, while the practical side of this research is application of an algorithm to determine the nearest neighbor indicators closes to the national poverty line in Iraq for 2012 | ||
| Keywords | ||
| the national poverty line | ||
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