Gold Price Prediction
DOI:
https://doi.org/10.5281/zenodo.6183215Keywords:
Machine Learning, Random Forest Regression, Linear Regression, PredictionAbstract
Gold is often used by investors as a barrier against
inflation or adverse economic times. As a result, it is critical for
investors to be able to accurately estimate gold prices. This
article is based on a study of gold price prediction by
relationship between gold price and selected factors influencing
it , namely date, stock value, current gold price ,united state oil
price, current silver price, currency medium(EUR/USD) using
Colab by random forest regression algorithm. Comparing and
Analyze R squared error graph and mean_absolute_error, and
with linear regression algorithm. Monthly price data for the
period January 2008 to May 2018 was used for the study. Two
machine learning algorithms random forest regression and
linear regression were used in analyzing these data. Random
forest regression, on the other hand, has been found to have
greater overall prediction accuracy