the classification task of data mining where prior outliers preprocessing is necessary. …

the financial indicators, using benchmark classification models. To confirm the performance of the proposed novel distance … indicators. For this reason, the proposed novel distance-based exponential moving-average (DBEMA) model is dynamically designed … to overcome the changing conditions of financial time series. A novel distance-based moving-average feature model can …

A distance between pairs of sets of autoregressive moving average (ARMA) processes is proposed. Its main properties are … discussed. The paper also shows how the proposed distance finds application in time series analysis. In particular it can be … used to evaluate the distance between portfolios of ARMA models or the distance between vector autoregressive (VAR) models. …

industry. Three DM-techniques were selected: Dependency Modeling, Change and Deviation Detection, and Classification. Of these … three techniques, two were found to be of complementary value in a PPM-context, Dependency modeling and Classification …

We propose multivariate classification as a statistical tool to describe business cycles. These cycles are often … economic variables. Multivariate classification overcomes these limitations by reducing dimension in a way suitable for human … potential of classification methods by determining the important economic variables (stylized facts) for the German business …

variables computed for the observations in the bootstrap sample are used as additional predictors for a classification tree. Two …