Creating a Training Set

    A training set is a collection of data to be used to train the neural network. There are two types of training sets commonly used with Encog.

• Supervised Training
• Unsupervised Training

    Supervised training data has both an input and expected output specified for the neural network. For example, the truth table above could be represented as a training set. There would be four rows, one for each of the combinations fed to the XOR operator. You would have two input columns and one output column. These correspond to the input and output neurons. The training sets are not concerned with hidden layers. Hidden layers are simply present to assist in learning.

    Unsupervised training data only has input values. There are no expected outputs. The neural network will train, in an unsupervised way, and determine for itself what the outputs should be. Unsupervised training is often used for classification problems where you want the neural network to group input data.

    First, we must create a training set. Select “Create Object” from the “Objects” menu. Select a training set. Once the training set has been created it will be added along with the network that was previously created.

Figure 4.8: The Newly Created Training Set

    Double clicking the training set will open it. The training set will open in a spreadsheet style window, as seen in Figure 4.9.

Figure 4.9: Editing the Training Set

    Here you can see the training set. By default, Encog creates a training set for XOR. This is just the default. Usually you would now create the desired number of input and output columns. However, because we are training the XOR operator, the data is fine as it is.