A refreshment

README.md

@@ -1 +1,65 @@
-Multi layer neural network implemented in several languages.
+# multi-layer-neural-network
+
+This is a multi-layer neural network library created in pure JavaScript. (still in development)
+
+## Usage:
+
+### Layer creation:
+```js
+const layer = NeuralNetwork.createLayer({
+    nodes: 2,
+    activation: 'sigmoid'
+});
+```
+
+### Neural Network initialization:
+```js
+const brain = NeuralNetwork.createNeuralNetwork({
+    inputNodes: 2,
+    layers: [
+        NeuralNetwork.createLayer({
+            nodes: 2,
+            activation: 'sigmoid'
+        }),
+        NeuralNetwork.createLayer({ // output layer
+            nodes: 1,
+            activation: 'sigmoid'
+        })
+    ],
+    learningRate: 0.1,
+});
+```
+
+### Training:
+```js
+const dataset = [
+    {
+        inputs: [0, 1],
+        targets: [1]
+    },
+    {
+        inputs: [1, 0],
+        targets: [1]
+    },
+    {
+        inputs: [1, 1],
+        targets: [0]
+    },
+    {
+        inputs: [0, 0],
+        targets: [0]
+    }
+];
+
+for(let i = 0; i < 10000; i++) { // how many times we want it to be trained
+    for(let data of dataset) {
+        brain.train(data.inputs, data.targets);
+    }
+}
+```
+
+### Predicting:
+```js
+const output = brain.predict([0, 1]);
+console.log(output);
+```

js/neuralnetwork.js

@@ -34,18 +34,7 @@ const NeuralNetwork = (function() {
 
         train(inputArray, targetArray) {
             const inputs = Matrix.from_arr(inputArray);
-
-            let prevLayerValues = inputs;
-
-            for(let layer of this.layers) {
-                layer.layerValues = Matrix.multiply(layer.weights, prevLayerValues);
-                layer.layerValues.add(layer.bias);
-                layer.layerValues.map(layer.activationFunction.func);
-
-                prevLayerValues = layer.layerValues;
-            }
-
-            const outputs = this.layers[this.layers.length - 1].layerValues;
+            const outputs = this.predict(inputArray);
             const targets = Matrix.from_arr(targetArray);
 
             let prevError = null;