PreceptronLearningRule.java

package perceptron;
import java.util.Arrays;

public class PreceptronLearningRule {
    public static void main(String args[]){
        double threshold = 1;
        double learningRate = 0.1;
        // Init weights
        double[] weights = {0.0, 0.0};
        
        // AND function Training data
        int[][][] trainingData = {
            {{0, 0}, {0}},
            {{0, 1}, {0}},
            {{1, 0}, {0}},
            {{1, 1}, {1}},
        };
        
        // Start training loop
        while(true){
            int errorCount = 0;
            // Loop over training data
            for(int i=0; i < trainingData.length; i++){
                System.out.println("Starting weights: " + Arrays.toString(weights));
                // Calculate weighted input
                double weightedSum = 0;
                for(int ii=0; ii < trainingData[i][0].length; ii++) {
                    weightedSum += trainingData[i][0][ii] * weights[ii];
                }

                // Calculate output
                int output = 0;
                if(threshold <= weightedSum){
                    output = 1;
                }

                System.out.println("Target output: " + trainingData[i][1][0] + ", "
                        + "Actual Output: " + output);
                                
                // Calculate error
                int error = trainingData[i][1][0] - output;
                
                // Increase error count for incorrect output
                if(error != 0){
                    errorCount++;
                }
                
                // Update weights
                for(int ii=0; ii < trainingData[i][0].length; ii++) {
                    weights[ii] += learningRate * error * trainingData[i][0][ii];
                }

                System.out.println("New weights: " + Arrays.toString(weights));
                System.out.println();
            }

            // If there are no errors, stop
            if(errorCount == 0){
                System.out.println("Final weights: " + Arrays.toString(weights));
                System.exit(0);
            }
        }
    }
}