bagging

Meta-Learning: Boosting and Bagging for Time Series Forecasting

I am always struggled to model the changes in gasoline prices as a categorical variable, especially in a small amount of time-series data. The answer to improving the performance of modeling such a dataset can be to combine more than one model. This method of combining and aggregating the predictions of multiple models is calledContinue reading “Meta-Learning: Boosting and Bagging for Time Series Forecasting”

Lagged Predictors in Regression Models and Improving by Bootstrapping and Bagging

Huge lines at gas stations have been seen around Turkey in recent days. Under the reason for this is the rise in the prices so often, in the last few months and the expectation to continue this. Of course, it is known that the rise in the exchange rate (US dollar to Turkish lira) hasContinue reading “Lagged Predictors in Regression Models and Improving by Bootstrapping and Bagging”

Feature Importance in Random Forest

The Turkish president thinks that high interest rates cause inflation, contrary to the traditional economic approach. For this reason, he dismissed two central bank chiefs within a year. And yes, unfortunately, the central bank officials have limited independence doing their job in Turkey contrary to the rest of the world. In order to check thatContinue reading “Feature Importance in Random Forest”

Bootstrapping Time Series for Gold Rush

Bootstrap aggregating (bagging), is a very useful averaging method to improve accuracy and avoids overfitting, in modeling the time series. It also helps stability so that we don’t have to do Box-Cox transformation to the data. Modeling time series data is difficult because the data are autocorrelated. In this case, moving block bootstrap (MBB) shouldContinue reading “Bootstrapping Time Series for Gold Rush”