Data mining with efficient genetic k-means

Because of the massive increase for streams available and being produced, the areas of data mining and machine learning have become increasingly popular. This takes place as companies, organizations and industries seek out optimal methods and techniques for processing these large data sets. Machine learning is a branch of artificial intelligence that involves creating programs that autonomously perform different data mining techniques when exposed to data streams. The study evaluates at two very different domains in an eort to provide a better and more optimized applicable method of clustering than is currently being used. We examine the use of data mining in healthcare, as well as the use of these techniques in the social media domain. Testing the proposed technique on these two drastically different domains offers us valuable insights into the performance of the proposed technique across domains.