The description problem of the clusters' centroids

The paper is devoted to analysis of the forecasting method for time series groups with the use of k-means clustering algorithm. The coordinates of the centers of clusters have been put in correspondence with summarizing time series data - the centroids of the clusters. A description of time series, the centroids of the clusters, is implemented with the use of forecasting models. It is suggested to use a common forecasting model, which is constructed for the cluster's centroid, in forecasting the individual time series in the cluster. The comparative analysis of the forecasting results with use of the classical Euclidean metric and the offered modified Euclid's metrics in the k-means clustering algorithm is made. The advantage of the offered modified Euclidean metric the metrics is shown.