title: How to choose the right amount of training dataset for forecasting?
body: <p>I have a dataset which has around 4 years of history data with weekly seasonality. I have started with taking the last 1 year as training dataset and forecasted about 30 data points. But reducing the training dataset to 6 months in some cases is giving me better forecasting values. </p>
  
  <p>Reading online, k fold cross validation seems to be one technique to identify the correct volume of training dataset. </p>
  
  <p>Am i correct on this? </p>
  
  <p>In general, can any one please recommend efficient ways to select the right amount of training dataset?</p>
  
  <p>Appreciate the help!</p>