01-introduction.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "hide_input": false,
        "id": "cR8plbkxCN3b"
      },
      "source": [
        "# 1장. 소개"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tuh069ZNCN3e"
      },
      "source": [
        "*아래 링크를 통해 이 노트북을 주피터 노트북 뷰어(nbviewer.org)로 보거나 구글 코랩(colab.research.google.com)에서 실행할 수 있습니다.*\n",
        "\n",
        "<table class=\"tfo-notebook-buttons\" align=\"left\">\n",
        "  <td>\n",
        "    <a target=\"_blank\" href=\"https://nbviewer.org/github/rickiepark/intro_ml_with_python_2nd_revised/blob/main/01-introduction.ipynb\"><img src=\"https://jupyter.org/assets/share.png\" width=\"60\" />주피터 노트북 뷰어로 보기</a>\n",
        "  </td>\n",
        "  <td>\n",
        "    <a target=\"_blank\" href=\"https://colab.research.google.com/github/rickiepark/intro_ml_with_python_2nd_revised/blob/main/01-introduction.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" />구글 코랩(Colab)에서 실행하기</a>\n",
        "  </td>\n",
        "</table>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "SAC9moCgCN3e"
      },
      "outputs": [],
      "source": [
        "# 노트북이 코랩에서 실행 중인지 체크합니다.\n",
        "import os\n",
        "import sys\n",
        "if 'google.colab' in sys.modules:\n",
        "    # 사이킷런 최신 버전을 설치합니다.\n",
        "    !pip install -q --upgrade scikit-learn\n",
        "    if not os.path.isdir('mglearn'):\n",
        "        # mglearn을 다운받고 압축을 풉니다.\n",
        "        !wget -q -O mglearn.tar.gz https://bit.ly/mglearn-tar-gz\n",
        "        !tar -xzf mglearn.tar.gz"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "hide_input": false,
        "id": "zzVzw5IgCN3g"
      },
      "outputs": [],
      "source": [
        "import sklearn\n",
        "from preamble import *"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fayuEloRCN3g"
      },
      "source": [
        "## 1.1 왜 머신 러닝인가?\n",
        "### 1.1.1 머신 러닝으로 풀 수 있는 문제\n",
        "### 1.1.2 문제와 데이터를 이해하기\n",
        "## 1.2 왜 파이썬인가?\n",
        "## 1.3 scikit-learn\n",
        "### 1.3.1 Scikit-learn 설치\n",
        "## 1.4 필수 라이브러리와 도구들\n",
        "### 1.4.1 주피터 노트북\n",
        "### 1.4.2 NumPy"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vmtSpzDYCN3g",
        "outputId": "b8b65e76-ee90-4c97-92db-3543f506a234",
        "uuid": "e2b8e959-75f0-4fa9-a878-5ab024f89223"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "x:\n",
            " [[1 2 3]\n",
            " [4 5 6]]\n"
          ]
        }
      ],
      "source": [
        "import numpy as np\n",
        "\n",
        "x = np.array([[1, 2, 3], [4, 5, 6]])\n",
        "print(\"x:\\n\", x)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ofxZQ9H_CN3h"
      },
      "source": [
        "### 1.4.3 SciPy"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mLxBZRAJCN3i",
        "outputId": "8bf98d74-8893-4b58-e058-1493b545b7b9"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "NumPy 배열:\n",
            " [[1. 0. 0. 0.]\n",
            " [0. 1. 0. 0.]\n",
            " [0. 0. 1. 0.]\n",
            " [0. 0. 0. 1.]]\n"
          ]
        }
      ],
      "source": [
        "from scipy import sparse\n",
        "\n",
        "# 대각선 원소는 1이고 나머지는 0인 2차원 NumPy 배열을 만듭니다.\n",
        "eye = np.eye(4)\n",
        "print(\"NumPy 배열:\\n\", eye)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mkygUONoCN3j",
        "outputId": "e97275b5-ffc3-4a3a-c121-d52560dd80f5"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "SciPy의 CSR 행렬:\n",
            "   (0, 0)\t1.0\n",
            "  (1, 1)\t1.0\n",
            "  (2, 2)\t1.0\n",
            "  (3, 3)\t1.0\n"
          ]
        }
      ],
      "source": [
        "# NumPy 배열을 CSR 포맷의 SciPy 희박 행렬로 변환합니다.\n",
        "# 0이 아닌 원소만 저장됩니다.\n",
        "sparse_matrix = sparse.csr_matrix(eye)\n",
        "print(\"\\nSciPy의 CSR 행렬:\\n\", sparse_matrix)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2DBMb1J_CN3j",
        "outputId": "720d6947-5e84-4185-ae7d-a8c921f9b69a"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "COO 표현:\n",
            "   (0, 0)\t1.0\n",
            "  (1, 1)\t1.0\n",
            "  (2, 2)\t1.0\n",
            "  (3, 3)\t1.0\n"
          ]
        }
      ],
      "source": [
        "data = np.ones(4)\n",
        "row_indices = np.arange(4)\n",
        "col_indices = np.arange(4)\n",
        "eye_coo = sparse.coo_matrix((data, (row_indices, col_indices)))\n",
        "print(\"COO 표현:\\n\", eye_coo)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GPmmBUylCN3k"
      },
      "source": [
        "### 1.4.4 matplotlib"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 430
        },
        "id": "ZH6SWV86CN3k",
        "outputId": "8e788d0c-f663-4421-f467-f94e73442559",
        "uuid": "30faf136-0ef7-4762-bd82-3795eea323d0"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n",
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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# -10에서 10까지 100개의 간격으로 나뉘어진 배열을 생성합니다.\n",
        "x = np.linspace(-10, 10, 100)\n",
        "# 사인 함수를 사용하여 y 배열을 생성합니다.\n",
        "y = np.sin(x)\n",
        "# plot 함수는 한 배열의 값을 다른 배열에 대응해서 선 그래프를 그립니다.\n",
        "plt.plot(x, y, marker=\"x\")\n",
        "plt.show() # 책에는 없음"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "F_93aqw-CN3k"
      },
      "source": [
        "### 1.4.5 pandas"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "_JsFxcEgCN3k",
        "outputId": "ee5e06a0-f286-4742-f0a5-de95b072a7f9",
        "scrolled": true,
        "uuid": "ad1b06f7-e03a-4938-9d59-5bb40e848553"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    Name  Location  Age\n",
              "0   John  New York   24\n",
              "1   Anna     Paris   13\n",
              "2  Peter    Berlin   53\n",
              "3  Linda    London   33"
            ],
            "text/html": [
              "\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "      <th>Location</th>\n",
              "      <th>Age</th>\n",
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              "      <th>0</th>\n",
              "      <td>John</td>\n",
              "      <td>New York</td>\n",
              "      <td>24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Anna</td>\n",
              "      <td>Paris</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Peter</td>\n",
              "      <td>Berlin</td>\n",
              "      <td>53</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Linda</td>\n",
              "      <td>London</td>\n",
              "      <td>33</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "    <div class=\"colab-df-buttons\">\n",
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              "      display:flex;\n",
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              "\n",
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              "      height: 32px;\n",
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              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
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              "\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-ac2dd1db-1c43-454f-b6f2-a964168ded76 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-ac2dd1db-1c43-454f-b6f2-a964168ded76');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-c465ea63-6843-45a3-a33d-461d85d19f74\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-c465ea63-6843-45a3-a33d-461d85d19f74')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-c465ea63-6843-45a3-a33d-461d85d19f74 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ],
      "source": [
        "import pandas as pd\n",
        "\n",
        "# 회원 정보가 들어간 간단한 데이터셋을 생성합니다.\n",
        "data = {'Name': [\"John\", \"Anna\", \"Peter\", \"Linda\"],\n",
        "        'Location' : [\"New York\", \"Paris\", \"Berlin\", \"London\"],\n",
        "        'Age' : [24, 13, 53, 33]\n",
        "       }\n",
        "\n",
        "data_pandas = pd.DataFrame(data)\n",
        "# 주피터 노트북은 Dataframe을 미려하게 출력해줍니다.\n",
        "data_pandas"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "id": "HtlJe_fkCN3l",
        "outputId": "f84ef7f8-aff1-4f5e-a499-e914b138bd11"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    Name Location  Age\n",
              "2  Peter   Berlin   53\n",
              "3  Linda   London   33"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-92827654-1f0c-4aa6-9fbe-eff06f0a6483\" class=\"colab-df-container\">\n",
              "    <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>Name</th>\n",
              "      <th>Location</th>\n",
              "      <th>Age</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Peter</td>\n",
              "      <td>Berlin</td>\n",
              "      <td>53</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Linda</td>\n",
              "      <td>London</td>\n",
              "      <td>33</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-92827654-1f0c-4aa6-9fbe-eff06f0a6483 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-92827654-1f0c-4aa6-9fbe-eff06f0a6483');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-78b968b0-5645-4ac0-acbc-dc5787f5f738\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-78b968b0-5645-4ac0-acbc-dc5787f5f738')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-78b968b0-5645-4ac0-acbc-dc5787f5f738 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ],
      "source": [
        "# Age 열의 값이 30 이상인 모든 행을 선택합니다.\n",
        "data_pandas[data_pandas.Age > 30]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "m1g6q2wpCN3l"
      },
      "source": [
        "### 1.4.6 mglearn"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6OPorlutCN3l"
      },
      "source": [
        "## 1.5 파이썬 2 vs. 파이썬 3\n",
        "## 1.6 이 책에서 사용하는 소프트웨어 버전"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IZRwxrs3CN3l",
        "outputId": "0bff738a-6edb-4479-b327-f0052ebbda1c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Python 버전: 3.10.12 (main, Jun 11 2023, 05:26:28) [GCC 11.4.0]\n",
            "pandas 버전: 1.5.3\n",
            "matplotlib 버전: 3.7.1\n",
            "NumPy 버전: 1.23.5\n",
            "SciPy 버전: 1.10.1\n",
            "IPython 버전: 7.34.0\n",
            "scikit-learn 버전: 1.3.0\n"
          ]
        }
      ],
      "source": [
        "import sys\n",
        "print(\"Python 버전:\", sys.version)\n",
        "\n",
        "import pandas as pd\n",
        "print(\"pandas 버전:\", pd.__version__)\n",
        "\n",
        "import matplotlib\n",
        "print(\"matplotlib 버전:\", matplotlib.__version__)\n",
        "\n",
        "import numpy as np\n",
        "print(\"NumPy 버전:\", np.__version__)\n",
        "\n",
        "import scipy as sp\n",
        "print(\"SciPy 버전:\", sp.__version__)\n",
        "\n",
        "import IPython\n",
        "print(\"IPython 버전:\", IPython.__version__)\n",
        "\n",
        "import sklearn\n",
        "print(\"scikit-learn 버전:\", sklearn.__version__)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rlP0gvBnCN3m"
      },
      "source": [
        "## 1.7 첫 번째 애플리케이션: 붓꽃의 품종 분류\n",
        "### 1.7.1 데이터 적재"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "id": "NBiaD_jtCN3m",
        "scrolled": true
      },
      "outputs": [],
      "source": [
        "from sklearn.datasets import load_iris\n",
        "iris_dataset = load_iris()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2UMBXHcjCN3m",
        "outputId": "573b3cb0-ceeb-41ec-ce63-9ad046622234"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "iris_dataset의 키:\n",
            " dict_keys(['data', 'target', 'frame', 'target_names', 'DESCR', 'feature_names', 'filename', 'data_module'])\n"
          ]
        }
      ],
      "source": [
        "print(\"iris_dataset의 키:\\n\", iris_dataset.keys())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "78TGXXoNCN3n",
        "outputId": "6212fc10-1b17-4fc2-db84-a0d5ea32aacb",
        "scrolled": true
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            ".. _iris_dataset:\n",
            "\n",
            "Iris plants dataset\n",
            "--------------------\n",
            "\n",
            "**Data Set Characteristics:**\n",
            "\n",
            "    :Number of Instances: 150 (50 in each of three classes)\n",
            "    :Number of Attributes: 4 numeric, pre\n",
            "...\n"
          ]
        }
      ],
      "source": [
        "print(iris_dataset['DESCR'][:193] + \"\\n...\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PxtEHq63CN3n",
        "outputId": "9db754f9-6105-47cd-b47d-f83a139ec216"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "타깃의 이름: ['setosa' 'versicolor' 'virginica']\n"
          ]
        }
      ],
      "source": [
        "print(\"타깃의 이름:\", iris_dataset['target_names'])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PJliOqoCCN3n",
        "outputId": "b896e14b-fec5-4e86-97f6-e796ebf48ed8"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "특성의 이름:\n",
            " ['sepal length (cm)', 'sepal width (cm)', 'petal length (cm)', 'petal width (cm)']\n"
          ]
        }
      ],
      "source": [
        "print(\"특성의 이름:\\n\", iris_dataset['feature_names'])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5sN7xsQFCN3n",
        "outputId": "6498d947-ba8c-4f1c-91fc-f85a900362d3"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "data의 타입: <class 'numpy.ndarray'>\n"
          ]
        }
      ],
      "source": [
        "print(\"data의 타입:\", type(iris_dataset['data']))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "77Em3vLlCN3n",
        "outputId": "d3583107-e879-471d-887a-a05598b6d250"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "data의 크기: (150, 4)\n"
          ]
        }
      ],
      "source": [
        "print(\"data의 크기:\", iris_dataset['data'].shape)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Eix8p25ACN3o",
        "outputId": "27c3b378-c050-4051-c7f5-7902a0e2e6b7"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "data의 처음 다섯 행:\n",
            " [[5.1 3.5 1.4 0.2]\n",
            " [4.9 3.  1.4 0.2]\n",
            " [4.7 3.2 1.3 0.2]\n",
            " [4.6 3.1 1.5 0.2]\n",
            " [5.  3.6 1.4 0.2]]\n"
          ]
        }
      ],
      "source": [
        "print(\"data의 처음 다섯 행:\\n\", iris_dataset['data'][:5])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RGipvmv0CN3o",
        "outputId": "6fed44cb-b124-490b-8745-4b4f3cd3dc09"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "target의 타입: <class 'numpy.ndarray'>\n"
          ]
        }
      ],
      "source": [
        "print(\"target의 타입:\", type(iris_dataset['target']))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Yy_GmKvtCN3o",
        "outputId": "1fe080c2-9bae-4c6e-ec7d-e2749bf9dd1d"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "target의 크기: (150,)\n"
          ]
        }
      ],
      "source": [
        "print(\"target의 크기:\", iris_dataset['target'].shape)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "S47e9RFgCN3o",
        "outputId": "8db38e15-fda8-4a22-facf-e5f3f0667e79"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "타깃:\n",
            " [0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            " 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
            " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2\n",
            " 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2\n",
            " 2 2]\n"
          ]
        }
      ],
      "source": [
        "print(\"타깃:\\n\", iris_dataset['target'])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "i2RzRnNICN3o"
      },
      "source": [
        "### 1.7.2 성과 측정: 훈련 데이터와 테스트 데이터"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "id": "pYi7UKK1CN3o"
      },
      "outputs": [],
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "X_train, X_test, y_train, y_test = train_test_split(\n",
        "    iris_dataset['data'], iris_dataset['target'], random_state=0)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-Pu3BsVPCN3p",
        "outputId": "d6bc3c1d-dce5-4470-a173-e8bc0b7dd726"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "X_train 크기: (112, 4)\n",
            "y_train 크기: (112,)\n"
          ]
        }
      ],
      "source": [
        "print(\"X_train 크기:\", X_train.shape)\n",
        "print(\"y_train 크기:\", y_train.shape)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D43d2Pu9CN3p",
        "outputId": "76daff53-b9dc-4e5a-fa5e-f3ca736c0bc6"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "X_test 크기: (38, 4)\n",
            "y_test 크기: (38,)\n"
          ]
        }
      ],
      "source": [
        "print(\"X_test 크기:\", X_test.shape)\n",
        "print(\"y_test 크기:\", y_test.shape)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Y8vl5JVXCN3p"
      },
      "source": [
        "### 1.7.3 가장 먼저 할 일: 데이터 살펴보기"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "hBl7LWVzCN3p",
        "outputId": "dd74340a-8261-42d2-a776-4173ce4c1fa5"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x1500 with 16 Axes>"
            ],
            "image/png": 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\n",
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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "# X_train 데이터를 사용해서 데이터프레임을 만듭니다.\n",
        "# 열의 이름은 iris_dataset.feature_names에 있는 문자열을 사용합니다.\n",
        "iris_dataframe = pd.DataFrame(X_train, columns=iris_dataset.feature_names)\n",
        "# 데이터프레임을 사용해 y_train에 따라 색으로 구분된 산점도 행렬을 만듭니다.\n",
        "pd.plotting.scatter_matrix(iris_dataframe, c=y_train, figsize=(15, 15), marker='o',\n",
        "                           hist_kwds={'bins': 20}, s=60, alpha=.8, cmap=mglearn.cm3)\n",
        "plt.show() # 책에는 없음"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EtOefn9pCN3q"
      },
      "source": [
        "### 1.7.4 첫 번째 머신 러닝 모델: k-최근접 이웃 알고리즘"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "metadata": {
        "id": "MOXCy5YGCN3q"
      },
      "outputs": [],
      "source": [
        "from sklearn.neighbors import KNeighborsClassifier\n",
        "knn = KNeighborsClassifier(n_neighbors=1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 74
        },
        "id": "lOI4LMFDCN3q",
        "outputId": "99e8ec0a-314a-46bd-84a7-03d1bb4da791"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "KNeighborsClassifier(n_neighbors=1)"
            ],
            "text/html": [
              "<style>#sk-container-id-1 {color: black;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>KNeighborsClassifier(n_neighbors=1)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">KNeighborsClassifier</label><div class=\"sk-toggleable__content\"><pre>KNeighborsClassifier(n_neighbors=1)</pre></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ],
      "source": [
        "knn.fit(X_train, y_train)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4GDYezDQCN3q"
      },
      "source": [
        "### 1.7.5 예측하기"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 29,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4YVCNU8NCN3q",
        "outputId": "0f05c9c7-dcbe-4592-ee00-1f86237b472f"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "X_new.shape: (1, 4)\n"
          ]
        }
      ],
      "source": [
        "X_new = np.array([[5, 2.9, 1, 0.2]])\n",
        "print(\"X_new.shape:\", X_new.shape)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "El-9zcaKCN3q",
        "outputId": "21d8cedc-0808-4544-f58b-857ce5e68b77"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "예측: [0]\n",
            "예측한 타깃의 이름: ['setosa']\n"
          ]
        }
      ],
      "source": [
        "prediction = knn.predict(X_new)\n",
        "print(\"예측:\", prediction)\n",
        "print(\"예측한 타깃의 이름:\",\n",
        "       iris_dataset['target_names'][prediction])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3Qsym5KMCN3q"
      },
      "source": [
        "### 1.7.6 모델 평가하기"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 31,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "moSUGtpjCN3r",
        "outputId": "a4aba719-229b-4e52-a49f-eaeab8021653"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "테스트 세트에 대한 예측값:\n",
            " [2 1 0 2 0 2 0 1 1 1 2 1 1 1 1 0 1 1 0 0 2 1 0 0 2 0 0 1 1 0 2 1 0 2 2 1 0\n",
            " 2]\n"
          ]
        }
      ],
      "source": [
        "y_pred = knn.predict(X_test)\n",
        "print(\"테스트 세트에 대한 예측값:\\n\", y_pred)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 32,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vIAII-eKCN3r",
        "outputId": "7d9424a2-c338-4a54-811c-0e0444488bda"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "테스트 세트의 정확도: 0.97\n"
          ]
        }
      ],
      "source": [
        "print(\"테스트 세트의 정확도: {:.2f}\".format(np.mean(y_pred == y_test)))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 33,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "B48pdu2mCN3r",
        "outputId": "4cd79555-2ffb-4a4c-c11e-da18e1ac7864"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "테스트 세트의 정확도: 0.97\n"
          ]
        }
      ],
      "source": [
        "print(\"테스트 세트의 정확도: {:.2f}\".format(knn.score(X_test, y_test)))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "n7HLWX73CN3r"
      },
      "source": [
        "## 1.8 요약"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 34,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nNkZ5MxPCN3r",
        "outputId": "89cecae5-6aba-44ce-a5f1-70260727b713"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "테스트 세트의 정확도: 0.97\n"
          ]
        }
      ],
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(\n",
        "    iris_dataset['data'], iris_dataset['target'], random_state=0)\n",
        "\n",
        "knn = KNeighborsClassifier(n_neighbors=1)\n",
        "knn.fit(X_train, y_train)\n",
        "\n",
        "print(\"테스트 세트의 정확도: {:.2f}\".format(knn.score(X_test, y_test)))"
      ]
    }
  ],
  "metadata": {
    "anaconda-cloud": {},
    "colab": {
      "name": "01-introduction.ipynb",
      "provenance": []
    },
    "environment": {
      "kernel": "python3",
      "name": "common-cpu.m102",
      "type": "gcloud",
      "uri": "gcr.io/deeplearning-platform-release/base-cpu:m102"
    },
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
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        "version": 3
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      "pygments_lexer": "ipython3",
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