add notebook

Techtonique · Feb 6, 2024 · 55e2f82 · 55e2f82
1 parent 4f2ccfd
commit 55e2f82
Showing 1 changed file with 73 additions and 30 deletions.
diff --git a/GPopt/demo/thierrymoudiki_20240206_tuning_BCN_classifier_Pt2.ipynb b/GPopt/demo/thierrymoudiki_20240206_tuning_BCN_classifier_Pt2.ipynb
@@ -12,21 +12,19 @@
     {
       "cell_type": "code",
       "execution_count": null,
-      "metadata": {},
+      "metadata": {
+        "id": "cxJzB_Pwry-O"
+      },
       "outputs": [],
       "source": [
-        "!pip uninstall -y BCN GPopt "
+        "!pip uninstall -y BCN GPopt"
       ]
     },
     {
       "cell_type": "code",
       "execution_count": null,
       "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "L7dr5u5k8hW9",
-        "outputId": "f26bd34b-d73b-4fee-b97a-3df46a0d8018"
+        "id": "L7dr5u5k8hW9"
       },
       "outputs": [],
       "source": [
@@ -37,11 +35,7 @@
       "cell_type": "code",
       "execution_count": null,
       "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "IBA5fko_BA4V",
-        "outputId": "122f3221-2fb1-409e-c4e8-17d9d1d8709c"
+        "id": "IBA5fko_BA4V"
       },
       "outputs": [],
       "source": [
@@ -79,7 +73,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 5,
       "metadata": {
         "id": "LIGGEBbxCznR"
       },
@@ -90,7 +84,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 6,
       "metadata": {
         "id": "fIgPu1vBAd7X"
       },
@@ -151,11 +145,7 @@
       "cell_type": "code",
       "execution_count": null,
       "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "dU2gF9rYC_Q_",
-        "outputId": "600a5854-6c32-4603-d8b4-d4c0d4a44263"
+        "id": "dU2gF9rYC_Q_"
       },
       "outputs": [],
       "source": [
@@ -174,20 +164,73 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "source": [
+        "print(res_opt.best_score)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "7xw2ii1auV6N",
+        "outputId": "050fce15-672d-466d-eb51-595b24d0bfad"
+      },
+      "execution_count": 19,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "-0.9857142857142858\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "res_opt.best_params[\"B\"] = int(res_opt.best_params[\"B\"])\n",
+        "res_opt.best_params[\"nu\"] = 10**res_opt.best_params[\"nu\"]\n",
+        "res_opt.best_params[\"lam\"] = 10**res_opt.best_params[\"lam\"]\n",
+        "res_opt.best_params[\"r\"] = 1 - 10**res_opt.best_params[\"r\"]\n",
+        "res_opt.best_params[\"tol\"] = 10**res_opt.best_params[\"tol\"]\n",
+        "res_opt.best_params[\"col_sample\"] = np.ceil(res_opt.best_params[\"col_sample\"])\n",
+        "res_opt.best_params[\"n_clusters\"] = np.ceil(res_opt.best_params[\"n_clusters\"])"
+      ],
       "metadata": {
-        "id": "zo4LTC_PDEGp"
+        "id": "sddAUZp5tEGw"
       },
-      "outputs": [],
+      "execution_count": 20,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 21,
+      "metadata": {
+        "id": "zo4LTC_PDEGp",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "0361a23c-ff05-4eb2-f4d4-6ed4f3ea5ed4"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "  |======================================================================| 100%\n",
+            "\n",
+            " Elapsed: 0.3253192901611328\n",
+            "\n",
+            "\n",
+            " Test set accuracy: 1.0\n",
+            "\n",
+            " Elapsed: 0.0092620849609375\n"
+          ]
+        }
+      ],
       "source": [
         "start = time()\n",
-        "estimator = bcn.BCNClassifier(B=int(parameters[0][0]),\n",
-        "                              nu=10**parameters[0][1],\n",
-        "                              lam=10**parameters[0][2],\n",
-        "                              r=1-10**parameters[0][3],\n",
-        "                              tol=10**parameters[0][4],\n",
-        "                              col_sample=np.ceil(parameters[0][5]),\n",
-        "                              n_clusters=np.ceil(parameters[0][6]),\n",
+        "estimator = bcn.BCNClassifier(**res_opt.best_params,\n",
         "                              activation=\"tanh\",\n",
         "                              type_optim=\"nlminb\").fit(X_train, y_train)\n",
         "print(f\"\\n Elapsed: {time() - start}\")\n",
@@ -220,4 +263,4 @@
   },
   "nbformat": 4,
   "nbformat_minor": 0
-}
+}