Update binary_logistic_regression_tf_with_hidden_layers.ipynb

Author: fs446

binary_logistic_regression_tf_with_hidden_layers.ipynb

@@ -123,6 +123,59 @@
     "print(\"X test dim\", X_test.shape, \"Y test dim\", Y_test.shape)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "b1955eac",
+   "metadata": {},
+   "source": [
+    "## Plot Data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "0d2bbfe0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plt.figure(figsize=(10, 5))\n",
+    "plt.subplot(1, 3, 1)\n",
+    "plt.plot(X[Y == 1, 0],\n",
+    "         X[Y == 1, 1],\n",
+    "         \"o\", color='orangered', ms=1)\n",
+    "plt.plot(X[Y == 0, 0],\n",
+    "         X[Y == 0, 1],\n",
+    "         \"o\", color='dodgerblue', ms=1)\n",
+    "plt.axis(\"square\")\n",
+    "plt.title(\"data '1' red and '0' blue\" + str(X.shape))\n",
+    "plt.xlabel(\"feature 1\")\n",
+    "plt.ylabel(\"feature 2\")\n",
+    "plt.axis([-10, 10, -10, 10])\n",
+    "plt.grid()\n",
+    "\n",
+    "plt.subplot(1, 3, 2)\n",
+    "plt.plot(X[Y == 1, 0],\n",
+    "         X[Y == 1, 1],\n",
+    "         \"o\", color='orangered', ms=1)\n",
+    "plt.axis(\"square\")\n",
+    "plt.title(\"data '1' red \" + str(X.shape))\n",
+    "plt.xlabel(\"feature 1\")\n",
+    "plt.ylabel(\"feature 2\")\n",
+    "plt.axis([-10, 10, -10, 10])\n",
+    "plt.grid()\n",
+    "\n",
+    "plt.subplot(1, 3, 3)\n",
+    "plt.plot(X[Y == 0, 0],\n",
+    "         X[Y == 0, 1],\n",
+    "         \"o\", color='dodgerblue', ms=1)\n",
+    "plt.axis(\"square\")\n",
+    "plt.title(\"data '0' blue \" + str(X.shape))\n",
+    "plt.xlabel(\"feature 1\")\n",
+    "plt.ylabel(\"feature 2\")\n",
+    "plt.axis([-10, 10, -10, 10])\n",
+    "plt.grid()"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "b23f6d44",
@@ -293,7 +346,7 @@
    "id": "9073cba9",
    "metadata": {},
    "source": [
-    "## Model Test"
+    "## Model Prediction"
    ]
   },
   {