Perceptron¶
Initializing a Perceptron¶
int num_inputs = 2;
int num_outputs = 1;
Perceptron pnn = new Perceptron(num_inputs, num_outputs);
Feeding Data through a Perceptron and receiving the Output¶
float[] inputs = new float[] {1, 0};
float[] outputs = pnn.feedforward(inputs);
System.out.println(outputs);
// gives : [0.5345]
Training a Perceptron¶
float[] answers = new float[] {1};
pnn.train_gradient_descent(inputs, answers);
System.out.println(pnn.feedforward(inputs));
// gives : [0.98799]
use momentum for training¶
considered as a faster way of training
float[] answers = new float[] {1};
pnn.train_momentum_gradient_descent(inputs, answers);
System.out.println(pnn.feedforward(inputs));
// gives : [0.98799]
Setting extra Variables¶
pnn.set_learning_rate(float);
pnn.set_momentum_rate(float);
pnn.set_print_interval(int);