Poincare Metric in Algorithms for Data Mining Tools

Today we cannot imagine life without computers. The massive use of the information communication technologies has produced large amounts of data that are difficult to interpret and use. With data mining tools and machine learning methods, large data sets can be processed and used for prediction and classification. This paper employees the well known classification algorithm the k nearest neighbour and it modified use the Poincare measurment distance instead of traditional Euclidean distance. The reason is that in different industries (economy, health, military . . .) it increasingly uses and stores databases of various images or photographs. When recognizing the similarity between two photographs, it is important that the algorithm recognizes certain patterns. Recognition is based on metrics. For this purposes an algorithm based on Poincare metric is tested on a data set of photos. A comparison was made on algorithm based on Euclidean metric.