machine-learning/human_learn_examples/human-learn examples.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "oriental-british",
   "metadata": {},
   "source": [
    "# Load data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "australian-pavilion",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:19:57.345423Z",
     "start_time": "2021-04-24T12:19:57.336645Z"
    }
   },
   "outputs": [],
   "source": [
    "from sklearn.datasets import load_iris\n",
    "from sklearn.model_selection import train_test_split\n",
    "import pandas as pd \n",
    "from hulearn.experimental.interactive import InteractiveCharts\n",
    "from hulearn.classification import InteractiveClassifier\n",
    "import datapane as dp \n",
    "import matplotlib.pylab as plt\n",
    "import pickle "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "portuguese-corruption",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:15:26.476964Z",
     "start_time": "2021-04-24T12:15:26.463549Z"
    }
   },
   "outputs": [],
   "source": [
    "X, y = load_iris(return_X_y=True, as_frame=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "limiting-documentary",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:15:26.500107Z",
     "start_time": "2021-04-24T12:15:26.498209Z"
    }
   },
   "outputs": [],
   "source": [
    "X.columns = ['sepal_length', 'sepal_width', 'petal_length', 'petal_width']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "herbal-stranger",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:15:28.288685Z",
     "start_time": "2021-04-24T12:15:28.282720Z"
    }
   },
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "introductory-superintendent",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:15:29.188027Z",
     "start_time": "2021-04-24T12:15:29.185064Z"
    }
   },
   "outputs": [],
   "source": [
    "train = pd.concat([X_train, pd.DataFrame(y_train)], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "apart-narrative",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T14:19:19.529357Z",
     "start_time": "2021-04-24T14:19:19.508579Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>6.5</td>\n",
       "      <td>2.8</td>\n",
       "      <td>4.6</td>\n",
       "      <td>1.5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>6.7</td>\n",
       "      <td>2.5</td>\n",
       "      <td>5.8</td>\n",
       "      <td>1.8</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>6.8</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.5</td>\n",
       "      <td>2.1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>6.0</td>\n",
       "      <td>2.2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>6.3</td>\n",
       "      <td>2.9</td>\n",
       "      <td>5.6</td>\n",
       "      <td>1.8</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>6.6</td>\n",
       "      <td>2.9</td>\n",
       "      <td>4.6</td>\n",
       "      <td>1.3</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>7.7</td>\n",
       "      <td>2.6</td>\n",
       "      <td>6.9</td>\n",
       "      <td>2.3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>5.7</td>\n",
       "      <td>3.8</td>\n",
       "      <td>1.7</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     sepal_length  sepal_width  petal_length  petal_width  target\n",
       "54            6.5          2.8           4.6          1.5       1\n",
       "108           6.7          2.5           5.8          1.8       2\n",
       "112           6.8          3.0           5.5          2.1       2\n",
       "17            5.1          3.5           1.4          0.3       0\n",
       "119           6.0          2.2           5.0          1.5       2\n",
       "103           6.3          2.9           5.6          1.8       2\n",
       "58            6.6          2.9           4.6          1.3       1\n",
       "118           7.7          2.6           6.9          2.3       2\n",
       "18            5.7          3.8           1.7          0.3       0\n",
       "4             5.0          3.6           1.4          0.2       0"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "swiss-knitting",
   "metadata": {},
   "source": [
    "# Draw"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "massive-russia",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:15:36.140916Z",
     "start_time": "2021-04-24T12:15:36.132545Z"
    }
   },
   "outputs": [
    {
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       "    </div>"
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     "output_type": "display_data"
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i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\n    if (force === true) {\n        display_loaded();\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(\"1002\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));",
      "application/vnd.bokehjs_load.v0+json": ""
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "charts = InteractiveCharts(train, labels='target')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "guilty-duration",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:15:38.412691Z",
     "start_time": "2021-04-24T12:15:38.345834Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.bokehjs_exec.v0+json": "",
      "text/html": [
       "\n",
       "<script id=\"1071\">\n",
       "  var xhr = new XMLHttpRequest()\n",
       "  xhr.responseType = 'blob';\n",
       "  xhr.open('GET', \"http://localhost:34327/autoload.js?bokeh-autoload-element=1071&bokeh-absolute-url=http://localhost:34327&resources=none\", true);\n",
       "  \n",
       "  xhr.onload = function (event) {\n",
       "    var script = document.createElement('script'),\n",
       "    src = URL.createObjectURL(event.target.response);\n",
       "    script.src = src;\n",
       "    document.body.appendChild(script);\n",
       "  };\n",
       "xhr.send();\n",
       "</script>"
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     "metadata": {
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       "server_id": "98a85e3d0d3241a082ac2eac6451d26c"
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     },
     "output_type": "display_data"
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   ],
   "source": [
    "charts.add_chart(x='sepal_length', y='sepal_width')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "legal-colors",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:17:05.812099Z",
     "start_time": "2021-04-24T12:17:05.796239Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "application/vnd.bokehjs_exec.v0+json": "",
      "text/html": [
       "\n",
       "<script id=\"1640\">\n",
       "  var xhr = new XMLHttpRequest()\n",
       "  xhr.responseType = 'blob';\n",
       "  xhr.open('GET', \"http://localhost:43243/autoload.js?bokeh-autoload-element=1640&bokeh-absolute-url=http://localhost:43243&resources=none\", true);\n",
       "  \n",
       "  xhr.onload = function (event) {\n",
       "    var script = document.createElement('script'),\n",
       "    src = URL.createObjectURL(event.target.response);\n",
       "    script.src = src;\n",
       "    document.body.appendChild(script);\n",
       "  };\n",
       "xhr.send();\n",
       "</script>"
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     "metadata": {
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       "server_id": "1706eb8762334deb85654a4107cbcf0f"
      }
     },
     "output_type": "display_data"
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   ],
   "source": [
    "charts.add_chart(x='petal_length', y='petal_width')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "2048fb28-dae7-4506-94ea-fccf657efcdc",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:17:38.213189Z",
     "start_time": "2021-04-24T12:17:38.193864Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.bokehjs_exec.v0+json": "",
      "text/html": [
       "\n",
       "<script id=\"1928\">\n",
       "  var xhr = new XMLHttpRequest()\n",
       "  xhr.responseType = 'blob';\n",
       "  xhr.open('GET', \"http://localhost:45547/autoload.js?bokeh-autoload-element=1928&bokeh-absolute-url=http://localhost:45547&resources=none\", true);\n",
       "  \n",
       "  xhr.onload = function (event) {\n",
       "    var script = document.createElement('script'),\n",
       "    src = URL.createObjectURL(event.target.response);\n",
       "    script.src = src;\n",
       "    document.body.appendChild(script);\n",
       "  };\n",
       "xhr.send();\n",
       "</script>"
      ]
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "server_id": "d88df4673f1d4e49adebbdb6f78108ac"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "charts.add_chart(x='sepal_length', y='petal_width')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "80d9a74b-55bc-4a08-8bca-d34023f0f6c0",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:18:31.798664Z",
     "start_time": "2021-04-24T12:18:31.774557Z"
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.bokehjs_exec.v0+json": "",
      "text/html": [
       "\n",
       "<script id=\"2372\">\n",
       "  var xhr = new XMLHttpRequest()\n",
       "  xhr.responseType = 'blob';\n",
       "  xhr.open('GET', \"http://localhost:33921/autoload.js?bokeh-autoload-element=2372&bokeh-absolute-url=http://localhost:33921&resources=none\", true);\n",
       "  \n",
       "  xhr.onload = function (event) {\n",
       "    var script = document.createElement('script'),\n",
       "    src = URL.createObjectURL(event.target.response);\n",
       "    script.src = src;\n",
       "    document.body.appendChild(script);\n",
       "  };\n",
       "xhr.send();\n",
       "</script>"
      ]
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "server_id": "1452fbcb4a0b4085861e42a25044a24c"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "charts.add_chart(x='petal_length', y='sepal_width')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "attended-washington",
   "metadata": {},
   "source": [
    "# Create model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "05d00cde-679d-4101-a7d3-c076a8e5fc89",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:20:03.011009Z",
     "start_time": "2021-04-24T12:20:03.005076Z"
    }
   },
   "outputs": [],
   "source": [
    "model = InteractiveClassifier(json_desc=charts.data())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "08f6a409-46ac-43c7-8d4a-f263a3a025df",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:20:04.179518Z",
     "start_time": "2021-04-24T12:20:04.109057Z"
    }
   },
   "outputs": [],
   "source": [
    "preds = model.fit(X_train, y_train).predict_proba(X_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "dental-portrait",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:20:04.690394Z",
     "start_time": "2021-04-24T12:20:04.670588Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape: (112, 3)\n",
      "Classes: [1, 2, 0]\n",
      "Predictions:\n",
      " [[5.71326574e-01 4.28530630e-01 1.42795945e-04]\n",
      " [2.00079952e-01 7.99720168e-01 1.99880072e-04]\n",
      " [2.00079952e-01 7.99720168e-01 1.99880072e-04]\n",
      " [2.49812641e-04 2.49812641e-04 9.99500375e-01]\n",
      " [4.99916708e-01 4.99916708e-01 1.66583375e-04]]\n"
     ]
    }
   ],
   "source": [
    "print('Shape:', preds.shape)\n",
    "print('Classes:', model.classes_)\n",
    "print('Predictions:\\n', preds[:5, :])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "231bff3f-fa7c-48bd-b0b1-b16fba602ed7",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:20:05.129846Z",
     "start_time": "2021-04-24T12:20:05.126427Z"
    },
    "code_folding": []
   },
   "outputs": [],
   "source": [
    "def scatter_plot_of_multiple_classes(columns: list):\n",
    "    col1, col2 = columns\n",
    "    plt.figure(figsize=(12, 3))\n",
    "    for i in range(3):\n",
    "        plt.subplot(131 + i)\n",
    "        plt.scatter(X_train[col1], X_train[col2], c=preds[:, i])\n",
    "        plt.xlabel(col1)\n",
    "        plt.ylabel(col2)\n",
    "        plt.title(model.classes_[i])\n",
    "        plt.colorbar()\n",
    "        plt.savefig('plot_prediction.png')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "undefined-reader",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:20:05.933498Z",
     "start_time": "2021-04-24T12:20:05.328556Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x216 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "scatter_plot_of_multiple_classes(['petal_length', 'petal_width'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "prescription-support",
   "metadata": {},
   "source": [
    "# Predict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "aggregate-policy",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:23:14.084597Z",
     "start_time": "2021-04-24T12:23:14.077931Z"
    }
   },
   "outputs": [],
   "source": [
    "new_sample = X_test.iloc[:1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "qualified-swing",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:23:24.119124Z",
     "start_time": "2021-04-24T12:23:24.109244Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>5.8</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    sepal_length  sepal_width  petal_length  petal_width\n",
       "14           5.8          4.0           1.2          0.2"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_sample"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "tamil-vehicle",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:23:28.323480Z",
     "start_time": "2021-04-24T12:23:28.312916Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[3.33000333e-04, 3.33000333e-04, 9.99333999e-01]])"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.predict_proba(new_sample)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "coordinated-logging",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:29:01.992321Z",
     "start_time": "2021-04-24T12:29:01.970920Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The prediction is 0\n",
      "The real label is 0\n"
     ]
    }
   ],
   "source": [
    "pred = model.predict(new_sample)\n",
    "real = y_test[:1]\n",
    "print(\"The prediction is\", pred[0])\n",
    "print(\"The real label is\", real.iloc[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "protective-investing",
   "metadata": {},
   "source": [
    "## Interpret the result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "moved-circle",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:30:36.593024Z",
     "start_time": "2021-04-24T12:30:36.590411Z"
    }
   },
   "outputs": [],
   "source": [
    "prediction_to_index = {0: 2, 1: 0, 2: 1}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "initial-spanking",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:36:12.187296Z",
     "start_time": "2021-04-24T12:36:12.175523Z"
    }
   },
   "outputs": [],
   "source": [
    "def plot_prediction(prediction: int, columns: list):\n",
    "    \"\"\"Plot new sample\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    prediction : int\n",
    "        prediction of the new sample\n",
    "    columns : list\n",
    "        Features to create a scatter plot \n",
    "    \"\"\"\n",
    "    \n",
    "    index = prediction_to_index[prediction] \n",
    "    col1, col2 = columns\n",
    "    \n",
    "    plt.figure(figsize=(12, 3))\n",
    "    plt.scatter(X_train[col1], X_train[col2], c=preds[:, index])\n",
    "    plt.plot(new_sample[col1], new_sample[col2], 'ro', c='red', label='new_sample')\n",
    "    \n",
    "    plt.xlabel(col1)\n",
    "    plt.ylabel(col2)\n",
    "    plt.title(f\"Label {model.classes_[index]}\")\n",
    "    plt.colorbar()\n",
    "    plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "august-hepatitis",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:36:12.642120Z",
     "start_time": "2021-04-24T12:36:12.412064Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_prediction(0, columns=['petal_length', 'petal_width'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "universal-jaguar",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:48:26.181280Z",
     "start_time": "2021-04-24T12:48:25.954340Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_prediction(0, columns=['sepal_length', 'sepal_width'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "optimum-columbus",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:49:22.450097Z",
     "start_time": "2021-04-24T12:49:22.182052Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_prediction(0, columns=['petal_length', 'sepal_width'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "minor-drilling",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:49:34.018392Z",
     "start_time": "2021-04-24T12:49:33.777645Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_prediction(0, columns=['sepal_length', 'petal_width'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "abstract-reading",
   "metadata": {},
   "source": [
    "# Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "optimum-sullivan",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:57:05.683048Z",
     "start_time": "2021-04-24T12:57:05.677497Z"
    }
   },
   "outputs": [],
   "source": [
    "from sklearn.metrics import confusion_matrix, f1_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "physical-proceeding",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:56:19.124413Z",
     "start_time": "2021-04-24T12:56:19.095266Z"
    }
   },
   "outputs": [],
   "source": [
    "predictions = model.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "cardiovascular-passion",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T14:03:06.616168Z",
     "start_time": "2021-04-24T14:03:06.601087Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[13,  0,  0],\n",
       "       [ 0, 15,  1],\n",
       "       [ 0,  0,  9]])"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "confusion_matrix(y_test, predictions, labels=[0,1,2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "nuclear-madagascar",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-04-24T12:58:44.799688Z",
     "start_time": "2021-04-24T12:58:44.788086Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
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