Research Based on Euclid Distance with Weights of K_means Algorithm

Euclid distance is commonly used to measure distance in the traditional k_means algorithm.The k_means algorithm based on weighted Euclid distance is researched and presented to overcome the existing problems of similarity calculation in clustering analysis based on traditional Euclid distance when we have no any domain knowledge about the data objects,the relative distance but not absolute distance is more accurately response to data distribution.Experiments on the standard database UCI show that the proposed method can produce a high accuracy clustering result.