چکیده مقاله
Machine learning methods to forecast are increasingly applying in different disciplines and are used in wide range of applications Predicting financial time series is achallenging area of forecasting in finance as well as machine learning The paper aims to compare a machine learning method nonlinear model and a linear forecasting method in gold price forecasting To do so, GMDH type Group Method of Data Handling neural network, as nonlinear method, which uses an evolutionary method and ARIMA forecasting model as a linear method are employed Our Results show that GMDH type neural network makes a better forecast in comparison with ARIMA model, based on MAPE and MPE criteria
کلیدواژهها
نویسندگان
Maryam Seifaddini
Assistant Professor of Computer Science at University of Guilan, Rasht, Iran
Mohammad Seidpisheh
Assistant Professor of Statistics at University of Guilan, Rasht, Iran
شیوه ارجاع
Seifaddini, Maryam and Seidpisheh, Mohammad,1398,Machine learning and Linear method Which Methods Provide Better Forecasts,3rd International Conference on Soft Computing,Rudsar
ارائهشده در
مجموعه مقالات سومین کنفرانس بین المللی محاسبات نرم29 آبان 1398 · رودسر