Simulated Neural Network with Bootstrapping Time Series Data
In the previous article, we examined the performances of covid-19 management of some developed countries and we found that the UK was slightly better than others. This time we are going to predict the spread of disease for about a month in the UK. The algorithm we will use for this purpose is the neuralContinue reading “Simulated Neural Network with Bootstrapping Time Series Data”
Comparing the Coronavirus Pandemic (COVID-19) Management for some Developed Countries
The pandemic continues at full speed in Turkey where I live, because the government doesn’t conduct the process well; the data they provide is so doubtful, and the decisions they made are very inconsistent. So, I wondered about the situation in the other part of the world, especially the developed countries. In order to that,Continue reading “Comparing the Coronavirus Pandemic (COVID-19) Management for some Developed Countries”
Dynamic Regression (ARIMA) vs. XGBoost
In the previous article, we mentioned that we were going to compare dynamic regression with ARIMA errors and the xgboost. Before doing that, let’s talk about dynamic regression. Time series modeling, most of the time, uses past observations as predictor variables. But sometimes, we need external variables that affect the target variables. To include thoseContinue reading “Dynamic Regression (ARIMA) vs. XGBoost”
Time Series Forecasting with XGBoost and Feature Importance
Those who follow my articles know that trying to predict gold prices has become an obsession for me these days. And I am also wondering which factors affect the prices. For the gold prices per gram in Turkey, are told that two factors determine the results: USA prices per ounce and exchange rate for theContinue reading “Time Series Forecasting with XGBoost and Feature Importance”
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