create Network and Training contracts

src/Phpml/NeuralNetwork/Network.php

@@ -0,0 +1,20 @@
+<?php
+
+declare (strict_types = 1);
+
+namespace Phpml\NeuralNetwork;
+
+interface Network extends Node
+{
+
+    /**
+     * @param mixed $input
+     */
+    public function setInput($input);
+
+    /**
+     * @return array
+     */
+    public function getLayers(): array;
+
+}

src/Phpml/NeuralNetwork/Network/LayeredNetwork.php

@@ -0,0 +1,36 @@
+<?php
+
+declare (strict_types = 1);
+
+namespace Phpml\NeuralNetwork\Network;
+
+use Phpml\NeuralNetwork\Network;
+
+abstract class LayeredNetwork implements Network
+{
+
+    /**
+     * @return array
+     */
+    public function getLayers(): array
+    {
+
+    }
+
+    /**
+     * @return float
+     */
+    public function getOutput(): float
+    {
+
+    }
+
+    /**
+     * @param mixed $input
+     */
+    public function setInput($input)
+    {
+
+    }
+
+}

src/Phpml/NeuralNetwork/Network/MultilayerPerceptron.php

@@ -0,0 +1,10 @@
+<?php
+
+declare (strict_types = 1);
+
+namespace Phpml\NeuralNetwork\Network;
+
+class MultilayerPerceptron extends LayeredNetwork
+{
+
+}

src/Phpml/NeuralNetwork/Training.php

@@ -0,0 +1,16 @@
+<?php
+
+declare (strict_types = 1);
+
+namespace Phpml\NeuralNetwork;
+
+interface Training
+{
+    /**
+     * @param array $samples
+     * @param array $targets
+     * @param float $desiredError
+     * @param int $maxIterations
+     */
+    public function train(array $samples, array $targets, float $desiredError = 0.001, int $maxIterations = 10000);
+}

src/Phpml/NeuralNetwork/Training/Backpropagation.php

@@ -0,0 +1,23 @@
+<?php
+
+declare (strict_types = 1);
+
+namespace Phpml\NeuralNetwork\Training;
+
+use Phpml\NeuralNetwork\Training;
+
+class Backpropagation implements Training
+{
+
+    /**
+     * @param array $samples
+     * @param array $targets
+     * @param float $desiredError
+     * @param int $maxIterations
+     */
+    public function train(array $samples, array $targets, float $desiredError = 0.001, int $maxIterations = 10000)
+    {
+
+    }
+
+}