update

Author: DavidVasilev1

_notebooks/2024-05-01-Percepteron.ipynb

@@ -97,15 +97,15 @@
     "    }\n",
     "\n",
     "    public static void main(String[] args) {\n",
-    "        double[][] X_train = {{0, 0}, {0, 1}, {1, 0}, {1, 1}};\n",
+    "        double[][] X_train = { {0, 0}, {0, 1}, {1, 0}, {1, 1} };\n",
     "        int[] y_train = {0, 0, 0, 1};\n",
     "\n",
     "        Perceptron perceptron = new Perceptron(2, 0.1);\n",
     "        perceptron.train(X_train, y_train, 100);\n",
     "\n",
     "        // Test the trained perceptron\n",
     "        System.out.println(\"Testing predictions:\");\n",
-    "        double[][] X_test = {{0, 0}, {0, 1}, {1, 0}, {1, 1}};\n",
+    "        double[][] X_test = { {0, 0}, {0, 1}, {1, 0}, {1, 1} };\n",
     "        for (double[] inputs : X_test) {\n",
     "            int prediction = perceptron.predict(inputs);\n",
     "            System.out.println(\"Inputs: \" + Arrays.toString(inputs) + \" Predicted: \" + prediction);\n",

_posts/2024-05-01-Percepteron_IPYNB_2_.md

@@ -67,15 +67,15 @@ public class Perceptron {
     }
 
     public static void main(String[] args) {
-        double[][] X_train = {{0, 0}, {0, 1}, {1, 0}, {1, 1}};
+        double[][] X_train = { {0, 0}, {0, 1}, {1, 0}, {1, 1} };
         int[] y_train = {0, 0, 0, 1};
 
         Perceptron perceptron = new Perceptron(2, 0.1);
         perceptron.train(X_train, y_train, 100);
 
         // Test the trained perceptron
         System.out.println("Testing predictions:");
-        double[][] X_test = {{0, 0}, {0, 1}, {1, 0}, {1, 1}};
+        double[][] X_test = { {0, 0}, {0, 1}, {1, 0}, {1, 1} };
         for (double[] inputs : X_test) {
             int prediction = perceptron.predict(inputs);
             System.out.println("Inputs: " + Arrays.toString(inputs) + " Predicted: " + prediction);