Hitachi Vantara Pentaho Community Wiki
Child pages
  • Using the Weka Forecasting Plugin
Skip to end of metadata
Go to start of metadata

You are viewing an old version of this page. View the current version.

Compare with Current View Page History

Version 1 Next »

1. Introduction

The Weka Forecasting plugin is a transformation step for PDI 4.x that is similar to the Weka Scoring Plugin. It can load or import a time series forecasting model created in Weka's time series analysis and forecasting environment and use it to generate a forecast for future time steps beyond the end of incoming historical data. This differs from the standard classification or regression scenario covered by the Weka Scoring plugin, where each incoming row receives a prediction (score) from the model, it that incoming rows provide a "window" over the recent history of the time series that the forecasting model then uses to initiate a closed-loop forecasting process to generate predictions for future time steps.

2 Requirements

The Weka Forecasting plugin requires PDI 4 or higher, Weka 3.7.3 or higher and the core time series forecasting library from the time series forecasting package. Both Weka and the time series forecasting core library are bundled with the plugin, so no further downloads are required.

3 Installation

Before starting Kettle's Spoon UI, the Weka Forecasting plugin must be installed in either the plugins/steps directory in your Kettle distribution or in $HOME/.kettle/plugins/steps. Simply unpack the distribution zip file into plugins/steps and then start Spoon.

4 Using the Weka Forecasting Plugin

  • No labels