CODEWITHSUNDEEP
machine-learningneural-networkencog
gcandal
gcandal

Reputation: 957

Encog query classification

I'm trying to process this dataset using Encog. In order to do so, I combined the outputs into one (can't seem to figure out how to use multiple expected outputs, even tho I unsuccessfully tried to manually train a NN with 4 output neurons) with the values: "disease1", "disease2", "none" and "both".

Starting from there, used the analyst wizard in the CSV, and the automatic process trained a NN with the expected outputs. A peak from the file:

"field:1","field:2","field:3","field:4","field:5","field:6","field:7","Output:field:7"
40.5,yes,yes,yes,yes,no,both,both
41.2,no,yes,yes,no,yes,second,second

Now my problem is: how do I query it? I tried with classification, but as far as I've understood, the result only gives me the values {0,1,2}, so there are two classes which I can't differentiate (both are 0).

This same problem applies to the Iris example presented in the wiki. Also, how does Encog extrapolate from the output neuron values to the 0/1/2 results?

Edit: the solution I have found was to use a separate network for disease 1 and disease 2, but I really would like to know if it was possible to combine those into one.

Upvotes: 2

Views: 852

Answers (1)

JeffHeaton
JeffHeaton

Reputation: 3278

You are correct, that you will need to combine the output column to a single value. Encog analyst will only classify to a single output column. That output column can have many different values. So normalizing the two output columns to none,first,second,both will work. If you use the underlying neural networks directly, you could actually train for two outputs each doing an independent classification. But for this discussion I will assume we are dealing with the analyst.

Are you querying the network using the workbench, or in code? By default Encog analyst encodes to the neural network using equilateral encoding. This results in a number of output neurons equal to n-1, where n is the number of classes. If you choose one-of-n encoding in the analyst wizard, then the regular classify method on the BasicNetwork will work, as it is only designed for one-of-n.

If you would like to query (in code) using equilateral, then you can use a method similar to the following. I am adding this to the next version of Encog.

/**
 * Used to classify a neural network that has been encoded using equilateral encoding.
 * This is the default for the Encog analyst. Equilateral encoding uses an output count
 * equal to the number of classes minus one.  
 * @param input The input to the neural network.
 * @param high The high value of the activation range, usually 1.
 * @param low The low end of the normalization range, usually -1 or 0. 
 * @return The class that the input belongs to.
 */
public int classifyEquilateral(final MLData input,double high, double low) {
    MLData result = this.compute(input);
    Equilateral eq = new Equilateral(getOutputCount()+1,high,low);
    return eq.decode(result.getData());
}

Upvotes: 2

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