Time Series Forecasting with WEKA

We have been discussing on Time series for while now. In this discussion, we are in the process of building the Cheat Sheet for Time Series that covers all aspects of Time Series. Earlier this month, a new cheat sheet version 4.5.0.1 was released. 

On this journey, we were looking at the features of different tools. We looked at the features of Microsoft SQL Server and Azure Machine Learning till now. In this post, we are looking at the Time Series forecasting features of Weka. 

The following figure shows the basic components of Weka for Time Series Forecasting. 

Weka is mainly looking at the regression techniques to support Time Series forecasting. In Weka, the lag feature is used to introduce the seasonality factor to the time series. There are many evaluation techniques in Weka Time series forecasting. 

Weka has the unique feature of specifying the not existence data which is missing in many other tools. For example, for a given holiday, stock data might not be available which is not missing data. Further, you can specify what are the missing data dates. Further, it has another unique feature where you can predict stepwise.