diff --git a/0-pilot-project/MNIST-kNN.ipynb b/0-pilot-project/MNIST-kNN.ipynb
index 8c21503..75d1754 100644
--- a/0-pilot-project/MNIST-kNN.ipynb
+++ b/0-pilot-project/MNIST-kNN.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "5a43420b",
+   "id": "5125f820",
    "metadata": {},
    "source": [
     "### Load MNIST dataset"
@@ -11,7 +11,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "ea54ab53",
+   "id": "4dbfbcbd",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -23,7 +23,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "d138914e",
+   "id": "bb0fae7c",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -35,7 +35,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "16c08d7d",
+   "id": "06585ea4",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -46,7 +46,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "259df665",
+   "id": "8d92fea0",
    "metadata": {},
    "outputs": [
     {
@@ -73,7 +73,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c32f3027",
+   "id": "288e3ba7",
    "metadata": {},
    "source": [
     "Bunch objects are sometimes used as an output for functions and methods. They extend dictionaries by enabling values to be accessed by key, bunch[\"value_key\"], or by an attribute, bunch.value_key.\\\n",
@@ -83,7 +83,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "0b2d3b38",
+   "id": "b171490e",
    "metadata": {},
    "outputs": [
     {
@@ -106,7 +106,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "026d00cb",
+   "id": "d45b18b4",
    "metadata": {},
    "outputs": [
     {
@@ -127,7 +127,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0045da2b",
+   "id": "07ebfb03",
    "metadata": {},
    "source": [
     "Datasets loaded by Scikit-Learn generally have a similar dictionary structure, including the following:\\\n",
@@ -139,7 +139,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "5bfb594c",
+   "id": "11f18ea2",
    "metadata": {},
    "outputs": [
     {
@@ -159,7 +159,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "322f80cf",
+   "id": "a7cf6de3",
    "metadata": {},
    "source": [
     "### Prepare the MNIST dataset"
@@ -167,7 +167,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5f1005a4",
+   "id": "cf0d7b65",
    "metadata": {},
    "source": [
     "$f(X) = y$\n",
@@ -181,7 +181,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "85354007",
+   "id": "1e953940",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -191,7 +191,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "id": "6e123fc5",
+   "id": "12769332",
    "metadata": {},
    "outputs": [
     {
@@ -212,7 +212,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "id": "570b4ca6",
+   "id": "4b7766d9",
    "metadata": {},
    "outputs": [
     {
@@ -233,7 +233,7 @@
   {
    "cell_type": "code",
    "execution_count": 11,
-   "id": "ad03b0c1",
+   "id": "385c1ec8",
    "metadata": {},
    "outputs": [
     {
@@ -253,7 +253,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "91c936b7",
+   "id": "cdea3089",
    "metadata": {},
    "source": [
     "### Plot data"
@@ -262,7 +262,7 @@
   {
    "cell_type": "code",
    "execution_count": 12,
-   "id": "cb6b5d57",
+   "id": "dc896a25",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -274,7 +274,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "id": "8896a0b3",
+   "id": "daa4382b",
    "metadata": {},
    "outputs": [
     {
@@ -297,7 +297,7 @@
   {
    "cell_type": "code",
    "execution_count": 14,
-   "id": "b108073e",
+   "id": "42938e91",
    "metadata": {},
    "outputs": [
     {
@@ -317,7 +317,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "id": "b4a8737d",
+   "id": "8c9ebb6b",
    "metadata": {},
    "outputs": [
     {
@@ -343,7 +343,7 @@
   {
    "cell_type": "code",
    "execution_count": 16,
-   "id": "323f527a",
+   "id": "1560264d",
    "metadata": {},
    "outputs": [
     {
@@ -364,7 +364,7 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "id": "507d99b3",
+   "id": "2755e361",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -375,7 +375,7 @@
   {
    "cell_type": "code",
    "execution_count": 18,
-   "id": "72250688",
+   "id": "d4fa3259",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -389,7 +389,7 @@
   {
    "cell_type": "code",
    "execution_count": 19,
-   "id": "b88a415e",
+   "id": "96bdd01c",
    "metadata": {},
    "outputs": [
     {
@@ -413,7 +413,7 @@
   {
    "cell_type": "code",
    "execution_count": 20,
-   "id": "dbb12d11",
+   "id": "92321904",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -429,7 +429,7 @@
   {
    "cell_type": "code",
    "execution_count": 21,
-   "id": "9e02d526",
+   "id": "f55b9f28",
    "metadata": {},
    "outputs": [
     {
@@ -454,7 +454,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d2d84b97",
+   "id": "16a7efd4",
    "metadata": {},
    "source": [
     "### Prepare data for machine learning"
@@ -463,7 +463,7 @@
   {
    "cell_type": "code",
    "execution_count": 22,
-   "id": "e16bb697",
+   "id": "729e023e",
    "metadata": {},
    "outputs": [
     {
@@ -484,7 +484,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3046819d",
+   "id": "71fc6692",
    "metadata": {},
    "source": [
     "### Train classifier"
@@ -492,142 +492,61 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
-   "id": "71d43c04",
+   "execution_count": 72,
+   "id": "09db3699",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "train_sz=   30, k= 1, accuracy=56.71%\n",
-      "train_sz=   30, k= 3, accuracy=44.19%\n",
-      "train_sz=   30, k= 5, accuracy=42.65%\n",
-      "train_sz=   30, k= 7, accuracy=36.24%\n",
-      "train_sz=   30, k= 9, accuracy=31.79%\n",
-      "train_sz=   30, k=11, accuracy=27.58%\n",
-      "train_sz=   30, k=13, accuracy=22.59%\n",
-      "train_sz=   30, k=15, accuracy=18.50%\n",
-      "train_sz=   30, k=17, accuracy=15.21%\n",
-      "train_sz=   30, k=19, accuracy=13.23%\n",
-      "train_sz=   30, k=21, accuracy=12.14%\n",
-      "train_sz=   30, k=23, accuracy=11.60%\n",
-      "train_sz=   30, k=25, accuracy=11.36%\n",
-      "train_sz=   30, k=27, accuracy=11.26%\n",
-      "train_sz=   30, k=29, accuracy=11.25%\n",
-      "train_sz=10030, k= 1, accuracy=94.64%\n",
-      "train_sz=10030, k= 3, accuracy=94.60%\n",
-      "train_sz=10030, k= 5, accuracy=94.53%\n",
-      "train_sz=10030, k= 7, accuracy=94.33%\n",
-      "train_sz=10030, k= 9, accuracy=94.06%\n",
-      "train_sz=10030, k=11, accuracy=93.84%\n",
-      "train_sz=10030, k=13, accuracy=93.60%\n",
-      "train_sz=10030, k=15, accuracy=93.42%\n",
-      "train_sz=10030, k=17, accuracy=93.22%\n",
-      "train_sz=10030, k=19, accuracy=93.09%\n",
-      "train_sz=10030, k=21, accuracy=92.91%\n",
-      "train_sz=10030, k=23, accuracy=92.74%\n",
-      "train_sz=10030, k=25, accuracy=92.53%\n",
-      "train_sz=10030, k=27, accuracy=92.39%\n",
-      "train_sz=10030, k=29, accuracy=92.22%\n",
-      "train_sz=20030, k= 1, accuracy=95.70%\n",
-      "train_sz=20030, k= 3, accuracy=95.76%\n",
-      "train_sz=20030, k= 5, accuracy=95.68%\n",
-      "train_sz=20030, k= 7, accuracy=95.54%\n",
-      "train_sz=20030, k= 9, accuracy=95.39%\n",
-      "train_sz=20030, k=11, accuracy=95.18%\n",
-      "train_sz=20030, k=13, accuracy=95.00%\n",
-      "train_sz=20030, k=15, accuracy=94.86%\n",
-      "train_sz=20030, k=17, accuracy=94.68%\n",
-      "train_sz=20030, k=19, accuracy=94.53%\n",
-      "train_sz=20030, k=21, accuracy=94.43%\n",
-      "train_sz=20030, k=23, accuracy=94.28%\n",
-      "train_sz=20030, k=25, accuracy=94.17%\n",
-      "train_sz=20030, k=27, accuracy=94.07%\n",
-      "train_sz=20030, k=29, accuracy=93.96%\n",
-      "train_sz=30030, k= 1, accuracy=96.33%\n",
-      "train_sz=30030, k= 3, accuracy=96.39%\n",
-      "train_sz=30030, k= 5, accuracy=96.34%\n",
-      "train_sz=30030, k= 7, accuracy=96.22%\n",
-      "train_sz=30030, k= 9, accuracy=96.00%\n",
-      "train_sz=30030, k=11, accuracy=95.91%\n",
-      "train_sz=30030, k=13, accuracy=95.73%\n",
-      "train_sz=30030, k=15, accuracy=95.58%\n",
-      "train_sz=30030, k=17, accuracy=95.44%\n",
-      "train_sz=30030, k=19, accuracy=95.34%\n",
-      "train_sz=30030, k=21, accuracy=95.16%\n",
-      "train_sz=30030, k=23, accuracy=95.05%\n",
-      "train_sz=30030, k=25, accuracy=94.99%\n",
-      "train_sz=30030, k=27, accuracy=94.84%\n",
-      "train_sz=30030, k=29, accuracy=94.77%\n",
-      "train_sz=40030, k= 1, accuracy=96.63%\n",
-      "train_sz=40030, k= 3, accuracy=96.70%\n",
-      "train_sz=40030, k= 5, accuracy=96.66%\n",
-      "train_sz=40030, k= 7, accuracy=96.54%\n",
-      "train_sz=40030, k= 9, accuracy=96.42%\n",
-      "train_sz=40030, k=11, accuracy=96.29%\n",
-      "train_sz=40030, k=13, accuracy=96.22%\n",
-      "train_sz=40030, k=15, accuracy=96.11%\n",
-      "train_sz=40030, k=17, accuracy=95.97%\n",
-      "train_sz=40030, k=19, accuracy=95.92%\n",
-      "train_sz=40030, k=21, accuracy=95.74%\n",
-      "train_sz=40030, k=23, accuracy=95.66%\n",
-      "train_sz=40030, k=25, accuracy=95.53%\n",
-      "train_sz=40030, k=27, accuracy=95.42%\n",
-      "train_sz=40030, k=29, accuracy=95.29%\n",
-      "train_sz=50030, k= 1, accuracy=96.89%\n",
-      "train_sz=50030, k= 3, accuracy=97.01%\n",
-      "train_sz=50030, k= 5, accuracy=96.91%\n",
-      "train_sz=50030, k= 7, accuracy=96.87%\n",
-      "train_sz=50030, k= 9, accuracy=96.78%\n",
-      "train_sz=50030, k=11, accuracy=96.73%\n",
-      "train_sz=50030, k=13, accuracy=96.54%\n",
-      "train_sz=50030, k=15, accuracy=96.48%\n",
-      "train_sz=50030, k=17, accuracy=96.38%\n",
-      "train_sz=50030, k=19, accuracy=96.35%\n",
-      "train_sz=50030, k=21, accuracy=96.30%\n",
-      "train_sz=50030, k=23, accuracy=96.15%\n",
-      "train_sz=50030, k=25, accuracy=96.06%\n",
-      "train_sz=50030, k=27, accuracy=95.98%\n",
-      "train_sz=50030, k=29, accuracy=95.92%\n",
-      "train_sz=60030, k= 1, accuracy=96.90%\n",
-      "train_sz=60030, k= 3, accuracy=97.04%\n",
-      "train_sz=60030, k= 5, accuracy=96.87%\n",
-      "train_sz=60030, k= 7, accuracy=96.93%\n",
-      "train_sz=60030, k= 9, accuracy=96.58%\n",
-      "train_sz=60030, k=11, accuracy=96.67%\n",
-      "train_sz=60030, k=13, accuracy=96.52%\n",
-      "train_sz=60030, k=15, accuracy=96.32%\n",
-      "train_sz=60030, k=17, accuracy=96.29%\n",
-      "train_sz=60030, k=19, accuracy=96.31%\n",
-      "train_sz=60030, k=21, accuracy=96.29%\n",
-      "train_sz=60030, k=23, accuracy=96.18%\n",
-      "train_sz=60030, k=25, accuracy=96.08%\n",
-      "train_sz=60030, k=27, accuracy=96.03%\n",
-      "train_sz=60030, k=29, accuracy=95.94%\n"
+      "train_sz=66652, k= 1, accuracy=98.7157%\n",
+      "train_sz=66652, k= 3, accuracy=98.7754%\n",
+      "train_sz=66652, k= 5, accuracy=98.7157%\n",
+      "train_sz=66652, k= 7, accuracy=98.6260%\n",
+      "train_sz=66652, k= 9, accuracy=98.5066%\n",
+      "train_sz=66652, k=11, accuracy=98.5663%\n",
+      "train_sz=66652, k=13, accuracy=98.5066%\n",
+      "train_sz=66652, k=15, accuracy=98.5066%\n",
+      "train_sz=66652, k=17, accuracy=98.3572%\n",
+      "train_sz=66652, k=19, accuracy=98.3871%\n",
+      "train_sz=66652, k=21, accuracy=98.3274%\n",
+      "train_sz=66652, k=23, accuracy=98.3572%\n",
+      "train_sz=66652, k=25, accuracy=98.4170%\n",
+      "train_sz=66652, k=27, accuracy=98.4170%\n",
+      "train_sz=66652, k=29, accuracy=98.3274%\n"
      ]
     }
    ],
    "source": [
     "from sklearn.neighbors import KNeighborsClassifier\n",
     "\n",
-    "max_k = 30\n",
-    "train_ranges = range(max_k, 70000, 10000)\n",
-    "kVals = range(1, max_k, 2)\n",
+    "# train_sz=60030, k= 3, accuracy=97.05%\n",
+    "# train_sz=67000, k= 3, accuracy=98.67%\n",
+    "# train_sz=66700, k= 3, accuracy=98.76%\n",
+    "# train_sz=66660, k= 3, accuracy=98.77%\n",
+    "# train_sz=66652, k= 3, accuracy=98.7754%\n",
+    "train_ranges = range(30, len(X), 10000)\n",
+    "kVals = range(1, 30, 2)\n",
     "accuracies = []\n",
     "classifier = KNeighborsClassifier()\n",
     "\n",
-    "for train_sz in train_ranges:\n",
-    "    # we use the first train_sz for training and test with the other images\n",
-    "    X_train, X_test, y_train, y_test = X[:train_sz], X[train_sz:], y[:train_sz], y[train_sz:]\n",
-    "    for k in kVals:\n",
-    "        # train the k-Nearest Neighbor classifier with the current value of `k`\n",
-    "        classifier = KNeighborsClassifier(n_neighbors=k)\n",
-    "        classifier.fit(X_train, y_train)\n",
-    "        # evaluate the model and update the accuracies list\n",
-    "        score = classifier.score(X_test, y_test)\n",
-    "        print(f\"train_sz={train_sz:5d}, k={k:2d}, accuracy={score*100:.2f}%\")\n",
-    "        accuracies.append(score)\n",
+    "X_train, X_test, y_train, y_test = X[:train_sz], X[train_sz:], y[:train_sz], y[train_sz:]\n",
+    "classifier = KNeighborsClassifier(n_neighbors=k)\n",
+    "classifier.fit(X_train, y_train)\n",
+    "score = classifier.score(X_test, y_test)\n",
+    "print(f\"train_sz={train_sz:5d}, k={k:2d}, accuracy={score*100:.4f}%\")\n",
+    "# for train_sz in train_ranges:\n",
+    "#     # we use the first train_sz for training and test with the other images\n",
+    "#     X_train, X_test, y_train, y_test = X[:train_sz], X[train_sz:], y[:train_sz], y[train_sz:]\n",
+    "#     for k in kVals:\n",
+    "#         # train the k-Nearest Neighbor classifier with the current value of `k`\n",
+    "#         classifier = KNeighborsClassifier(n_neighbors=k)\n",
+    "#         classifier.fit(X_train, y_train)\n",
+    "#         # evaluate the model and update the accuracies list\n",
+    "#         score = classifier.score(X_test, y_test)\n",
+    "#         print(f\"train_sz={train_sz:5d}, k={k:2d}, accuracy={score*100:.4f}%\")\n",
+    "#         accuracies.append(score)\n",
     "\n",
     "# import support vector machine\n",
     "# import sklearn.svm\n",
@@ -638,15 +557,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
-   "id": "a3e1c22a",
+   "execution_count": 69,
+   "id": "cee98962",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
+       "<Figure size 1440x1440 with 1 Axes>"
       ]
      },
      "metadata": {
@@ -656,26 +575,55 @@
     }
    ],
    "source": [
-    "import matplotlib.pyplot as plt\n",
+    "# import matplotlib.pyplot as plt\n",
     "\n",
-    "fig = plt.figure()\n",
-    "ax = fig.add_subplot(projection='3d')\n",
+    "# fig = plt.figure(figsize=(20, 20))\n",
+    "# ax = fig.add_subplot(121, projection='3d')\n",
     "\n",
-    "plot_train = np.array([i for i in train_ranges for _ in kVals])\n",
-    "plot_kVals = np.array([i for _ in train_ranges for i in kVals])\n",
+    "# _train, _kVals = np.meshgrid(train_ranges, kVals)\n",
+    "# _train, _kVals = _train.ravel(), _kVals.ravel()\n",
     "\n",
+    "# top = accuracies-min(accuracies)\n",
+    "# bottom = np.full_like(top,min(accuracies))\n",
+    "# width = 1000\n",
+    "# depth = 2\n",
     "\n",
-    "ax.plot(plot_train, plot_kVals, np.array(accuracies))\n",
-    "ax.set_xlabel(\"Train_size\")\n",
-    "ax.set_ylabel(\"k\")\n",
-    "ax.set_zlabel(\"accuracy\")\n",
-    "fig.show()"
+    "# colors = ['#ffffff', '#b3dce2', '#9fd3de', '#8ccada', '#7bc3d7', '#66b9d2']\n",
+    "# ax.bar3d(x=_train, y=_kVals, z=bottom, dx=width, dy=depth, dz=top, color='#66b9d2',shade=True)\n",
+    "# ax.set_zlim3d((min(accuracies),max(accuracies)))\n",
+    "\n",
+    "# ax.set_xlabel(\"Train_size\")\n",
+    "# ax.set_ylabel(\"k\")\n",
+    "# ax.set_zlabel(\"accuracy\")\n",
+    "\n",
+    "# fig.show()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
-   "id": "eecb54d6",
+   "execution_count": 70,
+   "id": "659bae0d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.9877538829151732"
+      ]
+     },
+     "execution_count": 70,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "max(accuracies)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 82,
+   "id": "d37de857",
    "metadata": {},
    "outputs": [
     {
@@ -699,8 +647,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
-   "id": "12e68bca",
+   "execution_count": 83,
+   "id": "9f6804c8",
    "metadata": {},
    "outputs": [
     {
@@ -718,8 +666,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
-   "id": "d25b4012",
+   "execution_count": 84,
+   "id": "9c3ef940",
    "metadata": {},
    "outputs": [
     {
@@ -737,8 +685,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
-   "id": "9c9a6afe",
+   "execution_count": 85,
+   "id": "8221555f",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -748,8 +696,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
-   "id": "0c230c0f",
+   "execution_count": 86,
+   "id": "3d36bc28",
    "metadata": {},
    "outputs": [
     {
@@ -758,7 +706,7 @@
        "array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=uint8)"
       ]
      },
-     "execution_count": 32,
+     "execution_count": 86,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -770,7 +718,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "560efd6a",
+   "id": "ee904ff4",
    "metadata": {},
    "source": [
     "### Evaluation"
@@ -778,36 +726,36 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
-   "id": "894a0b6f",
+   "execution_count": 88,
+   "id": "cf17fb24",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy Train 96.24854239546893\n"
+      "Accuracy Train 98.66020524515393\n"
      ]
     }
    ],
    "source": [
     "# trainings accuracy\n",
-    "wrong_images = X_train[(csict(X_train)-y_train) != 0]\n",
+    "wrong_images = X_train[(classifier.predict(X_train)-y_train) != 0]\n",
     "percentage = ((1-len(wrong_images)/len(X_train)) * 100)\n",
     "print(\"Accuracy Train \" + str(percentage))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
-   "id": "61f770dc",
+   "execution_count": 89,
+   "id": "70034cf7",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Accuracy Test 95.93781344032097\n"
+      "Accuracy Test 98.77538829151732\n"
      ]
     }
    ],
@@ -820,7 +768,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6adaaccc",
+   "id": "3975899b",
    "metadata": {},
    "source": [
     "Accuracy is strongly influenced by the distribution of the classes in the test data."
@@ -828,7 +776,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a412d401",
+   "id": "bd89f794",
    "metadata": {},
    "source": [
     "#### Cross Validation\n",
@@ -837,15 +785,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
-   "id": "f62a53ac",
+   "execution_count": 90,
+   "id": "9be7442c",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[0.95112444 0.95077461 0.95322339]\n"
+      "[0.96930417 0.96898771 0.96498177]\n"
      ]
     }
    ],
@@ -858,15 +806,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
-   "id": "b29ea8f6",
+   "execution_count": 91,
+   "id": "5c0317f5",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[5 0 4 ... 4 0 1]\n"
+      "[5 0 4 ... 8 9 5]\n"
      ]
     }
    ],
@@ -880,7 +828,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fd8a72db",
+   "id": "06da2cde",
    "metadata": {},
    "source": [
     "#### Precision"
@@ -888,17 +836,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
-   "id": "abe435e9",
+   "execution_count": 92,
+   "id": "473e073d",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "0.9526968189412931"
+       "0.9679281746772196"
       ]
      },
-     "execution_count": 46,
+     "execution_count": 92,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -911,7 +859,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3233385e",
+   "id": "3e0c1a22",
    "metadata": {},
    "source": [
     "#### Recall"
@@ -919,17 +867,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
-   "id": "5c8a9c0b",
+   "execution_count": 93,
+   "id": "6763d555",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "0.9517074795935365"
+       "0.9677579067394827"
       ]
      },
-     "execution_count": 47,
+     "execution_count": 93,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -942,7 +890,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e491c479",
+   "id": "b7acbde2",
    "metadata": {},
    "source": [
     "#### F1 Score"
@@ -950,17 +898,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
-   "id": "aed52544",
+   "execution_count": 94,
+   "id": "9a3e7b6e",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "0.9516064433898149"
+       "0.9676787940700043"
       ]
      },
-     "execution_count": 48,
+     "execution_count": 94,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -973,7 +921,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b2aefea8",
+   "id": "18beba4a",
    "metadata": {},
    "source": [
     "#### Confusion Matrix"
@@ -981,24 +929,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
-   "id": "49c6b21d",
+   "execution_count": 95,
+   "id": "ae3cad3f",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[5863    7    5    2    0   11   30    2    4    4]\n",
-      " [   0 6694   15    5   10    0    5   11    1    5]\n",
-      " [  66  149 5496   28   15    7   21  135   29   13]\n",
-      " [  13   45   32 5804    3   75    9   64   44   43]\n",
-      " [   6   90    1    1 5522    0   29   15    3  180]\n",
-      " [  24   42    3   86   14 5112   72    7   13   51]\n",
-      " [  38   22    2    0    4   30 5823    0    2    0]\n",
-      " [   7  124   13    2   24    1    0 6003    1   93]\n",
-      " [  28  147   22  125   35  131   38   27 5182  116]\n",
-      " [  25   33    5   70   49   10    3  116   11 5632]]\n"
+      "[[6516    2    6    0    1    7   17    2    4    3]\n",
+      " [   2 7457   10    2    2    1    4   11    3    4]\n",
+      " [  54   63 6379   22    7    3    7   99   17    6]\n",
+      " [  12   19   44 6534    2   75    4   37   40   29]\n",
+      " [   9   59    1    1 6276    0   16   11    3  126]\n",
+      " [  26   12    5   86   10 5774   62    4   21   27]\n",
+      " [  31   12    2    0    9   22 6462    0    2    0]\n",
+      " [   4   78   17    3   23    2    0 6743    3   67]\n",
+      " [  32   77   34   93   43  109   29   16 6014   58]\n",
+      " [  27   17    8   50   74   14    4   81    8 6348]]\n"
      ]
     }
    ],
@@ -1011,44 +959,44 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
-   "id": "373dcc20",
+   "execution_count": 96,
+   "id": "6bff7f05",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[[9.89035088e-01 1.18083671e-03 8.43454791e-04 3.37381916e-04\n",
-      "  0.00000000e+00 1.85560054e-03 5.06072874e-03 3.37381916e-04\n",
-      "  6.74763833e-04 6.74763833e-04]\n",
-      " [0.00000000e+00 9.92291728e-01 2.22353988e-03 7.41179958e-04\n",
-      "  1.48235992e-03 0.00000000e+00 7.41179958e-04 1.63059591e-03\n",
-      "  1.48235992e-04 7.41179958e-04]\n",
-      " [1.10756838e-02 2.50041953e-02 9.22302400e-01 4.69877496e-03\n",
-      "  2.51720087e-03 1.17469374e-03 3.52408122e-03 2.26548079e-02\n",
-      "  4.86658835e-03 2.18157409e-03]\n",
-      " [2.12002609e-03 7.33855186e-03 5.21852577e-03 9.46510111e-01\n",
-      "  4.89236791e-04 1.22309198e-02 1.46771037e-03 1.04370515e-02\n",
-      "  7.17547293e-03 7.01239400e-03]\n",
-      " [1.02616727e-03 1.53925090e-02 1.71027878e-04 1.71027878e-04\n",
-      "  9.44415940e-01 0.00000000e+00 4.95980845e-03 2.56541816e-03\n",
-      "  5.13083633e-04 3.07850180e-02]\n",
-      " [4.42477876e-03 7.74336283e-03 5.53097345e-04 1.58554572e-02\n",
-      "  2.58112094e-03 9.42477876e-01 1.32743363e-02 1.29056047e-03\n",
-      "  2.39675516e-03 9.40265487e-03]\n",
-      " [6.41783483e-03 3.71558858e-03 3.37780780e-04 0.00000000e+00\n",
-      "  6.75561561e-04 5.06671170e-03 9.83448742e-01 0.00000000e+00\n",
-      "  3.37780780e-04 0.00000000e+00]\n",
-      " [1.11678366e-03 1.97830249e-02 2.07402680e-03 3.19081047e-04\n",
-      "  3.82897256e-03 1.59540523e-04 0.00000000e+00 9.57721761e-01\n",
-      "  1.59540523e-04 1.48372687e-02]\n",
-      " [4.78550675e-03 2.51239104e-02 3.76004102e-03 2.13638694e-02\n",
-      "  5.98188344e-03 2.23893352e-02 6.49461630e-03 4.61459580e-03\n",
-      "  8.85660571e-01 1.98256708e-02]\n",
-      " [4.19885791e-03 5.54249244e-03 8.39771582e-04 1.17568021e-02\n",
-      "  8.22976150e-03 1.67954316e-03 5.03862949e-04 1.94827007e-02\n",
-      "  1.84749748e-03 9.45918710e-01]]\n"
+      "[[9.93595608e-01 3.04971028e-04 9.14913083e-04 0.00000000e+00\n",
+      "  1.52485514e-04 1.06739860e-03 2.59225374e-03 3.04971028e-04\n",
+      "  6.09942056e-04 4.57456542e-04]\n",
+      " [2.66808965e-04 9.94797225e-01 1.33404482e-03 2.66808965e-04\n",
+      "  2.66808965e-04 1.33404482e-04 5.33617930e-04 1.46744931e-03\n",
+      "  4.00213447e-04 5.33617930e-04]\n",
+      " [8.11176205e-03 9.46372240e-03 9.58239447e-01 3.30479195e-03\n",
+      "  1.05152471e-03 4.50653447e-04 1.05152471e-03 1.48715638e-02\n",
+      "  2.55370287e-03 9.01306895e-04]\n",
+      " [1.76574456e-03 2.79576221e-03 6.47439670e-03 9.61447911e-01\n",
+      "  2.94290759e-04 1.10359035e-02 5.88581519e-04 5.44437905e-03\n",
+      "  5.88581519e-03 4.26721601e-03]\n",
+      " [1.38418948e-03 9.07413104e-03 1.53798831e-04 1.53798831e-04\n",
+      "  9.65241464e-01 0.00000000e+00 2.46078130e-03 1.69178714e-03\n",
+      "  4.61396493e-04 1.93786527e-02]\n",
+      " [4.31392069e-03 1.99104032e-03 8.29600133e-04 1.42691223e-02\n",
+      "  1.65920027e-03 9.58022233e-01 1.02870416e-02 6.63680106e-04\n",
+      "  3.48432056e-03 4.47984072e-03]\n",
+      " [4.74006116e-03 1.83486239e-03 3.05810398e-04 0.00000000e+00\n",
+      "  1.37614679e-03 3.36391437e-03 9.88073394e-01 0.00000000e+00\n",
+      "  3.05810398e-04 0.00000000e+00]\n",
+      " [5.76368876e-04 1.12391931e-02 2.44956772e-03 4.32276657e-04\n",
+      "  3.31412104e-03 2.88184438e-04 0.00000000e+00 9.71613833e-01\n",
+      "  4.32276657e-04 9.65417867e-03]\n",
+      " [4.91929285e-03 1.18370484e-02 5.22674865e-03 1.42966949e-02\n",
+      "  6.61029977e-03 1.67563413e-02 4.45810915e-03 2.45964643e-03\n",
+      "  9.24519600e-01 8.91621829e-03]\n",
+      " [4.07178404e-03 2.56371588e-03 1.20645453e-03 7.54034082e-03\n",
+      "  1.11597044e-02 2.11129543e-03 6.03227266e-04 1.22153521e-02\n",
+      "  1.20645453e-03 9.57321671e-01]]\n"
      ]
     }
    ],
@@ -1059,8 +1007,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
-   "id": "b239a737",
+   "execution_count": 97,
+   "id": "0d655587",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1070,13 +1018,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
-   "id": "849572b4",
+   "execution_count": 98,
+   "id": "1c951c80",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 720x504 with 2 Axes>"
       ]
@@ -1100,7 +1048,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ee19282c",
+   "id": "789dc78c",
    "metadata": {},
    "source": [
     "## Train kNN Classifer\n",
@@ -1110,7 +1058,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "a0c32f85",
+   "id": "4a7bc22f",
    "metadata": {},
    "outputs": [],
    "source": []