Getting Started

The exercises can be started by clicking the Getting Started button on the Tip of the Day or using the menu command Help > Getting Started...

 

1. Pressure

In the first exercise you will forecast a future health problem.

The 'Pressure.tvq' sample is a record of a patient's blood pressure taken every day. The systolic and diastolic pressures vary quite significantly and they do not always rise and fall together. The patient needs to know if a problem is likely to occur any time in the near future. The systolic column and diastolic columns are changed to Serial to make the grid ready to allow rows and future values to be added and tested. 'Action > Forecast' opens the 'Forecast' dialog. New rows are generated with the forecasted values. The grid scrolls to show the new rows. The graph of the forecasted systolic values show a future high blood pressure problem.

 

2. Random

This exercise shows that SwingNN can find trends and forecast future values even if the data is random. All the columns are already set to 'Serial' so future values can be forecasted. When forecasting has finished the risk values are indicated. The forecast value may be wrong for any risk. That is to be expected when the initial values are random. SwingNN shows you the risk.

 

3. Grocer

Every day a retail grocer collects his stock from the wholesale market and sets the prices he will charge. SwingNN is used to forecast the prices that he will be charging in the next few days. All the columns are set to 'Input'. The columns for the food prices that are to be forecast to changed to 'Serial'. The 'Forecast' toolbar icon is enabled and is clicked to open the 'Forecast' dialog. 'Values to forecast' is changed to 5 and forecasting started. When forecasting has finished the next days food prices may show some low risk bargains that could be used as sales leaders without any serious impact on the grocers profit.

 

4. Shares

Many applications use neural networks to forecast the price of shares. The forecasts are often less useful than those of stock market experts. This exercise shows that the forecast produced by SwingNN is a downward price trend. The expert forecasted a similar downward trend.