HexaD_DataCleanup_Classification.ipynb

{
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  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyPFqpN9KmPdJoPwe7O7LSaV",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/CSID-DGU/2024-1-CECD1-HexaD-7/blob/feature/HexaD_DataCleanup_Classification.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "***뉴스 기사 형식 분류를 위한 분류모델 테스팅***\n",
        "\n",
        "      (1) 적은 데이터로 빠르게 형식 분류 가능성을 테스팅해보기 위해 나이브베이즈 분류모델을 사용하였다.\n",
        "\n",
        "      (2) 모델학습을 위한 크롤링 데이터의 개수는 각 스트레이트기사 199개,기획기사 199개,보도기사 157개를 사용했다.\n",
        "\n",
        "\n",
        "      (3) 해당 코드는 크롤링한 기사를 바탕으로한 데이터 전처리 및 분류모델 학습과 테스팅에 대한 코드를 포함한다.\n",
        "\n",
        "      헬스경향사의 기사 형식별 분류 매칭은 아래 표와 같다."
      ],
      "metadata": {
        "id": "wyLDgAyrUqWw"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        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)"
      ],
      "metadata": {
        "id": "83_UA28R8EZG"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 66,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ngvPZvKj6VrE",
        "outputId": "3ea996e1-add9-4426-d41e-8c08d85fa5af"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Tags\n",
            "스트레이트    199\n",
            "기획       199\n",
            "보도       157\n",
            "Name: count, dtype: int64\n"
          ]
        }
      ],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "#crawling data 불러오기\n",
        "#df = pd.read_csv('article_news_policy.csv')\n",
        "df = pd.read_csv('test.csv', encoding = \"CP949\", engine='python')\n",
        "\n",
        "df['Content'].head(500)\n",
        "df['Tags'].head(500)\n",
        "\n",
        "# 각 레이블의 개수\n",
        "tag_counts = df['Tags'].value_counts()\n",
        "print(tag_counts)\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "3vLd2IvEUl1G"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "[크롤링 데이터 전처리 진행]\n",
        "\n",
        "*   null값 샘플 제거, 중복 데이터 제거\n",
        "*   한글 외에 데이터 정규표현식 이용하여 전부 제거\n",
        "*   토큰화 수행\n",
        "*   불용어 제거\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "OaLkO86L7Ra-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 정규표현식을 이용해 한글, 숫자 외 문자 제거.\n",
        "df['Content'] = df['Content'].str.replace(\"[^ㄱ-ㅎㅏ-ㅣ가-힣\\d ]\", \"\", regex=True)\n",
        "\n",
        "\n",
        "print('샘플 개수:', len(df))\n",
        "\n",
        "#null값을 갖는 튜플 제거\n",
        "df = df.dropna(subset=['Content'])\n",
        "print('null값 제거 후 샘플 개수:', len(df))\n",
        "\n",
        "#중복 기사 제거\n",
        "df = df.drop_duplicates(subset=['Content'])\n",
        "\n",
        "print('중복 제거 후 샘플 개수:', len(df))\n",
        "\n",
        "\n",
        "df['Content'].head(10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9m4tp2kI6jVd",
        "outputId": "29aade8d-4059-4ac2-8a0b-644cfd394ca7"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "샘플 개수: 2699\n",
            "null값 제거 후 샘플 개수: 555\n",
            "중복 제거 후 샘플 개수: 435\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    가천대 길병원은 26일 저스트병원과 진료협력을 위한 협약을 맺었다고 밝혔다 협약식에...\n",
              "1    가톨릭대 인천성모병원은 오늘29일 이형섭구정순 부부가 병원발전기금 3억원을 기부했다...\n",
              "2    분당서울대병원은 24일 미국   이하 재단과 미국 로스앤젤레스에 한국형 건강검진센터...\n",
              "3    서울대치과병원 중앙장애인구강진료센터이하 중앙센터는 제44회 장애인의 날을 맞아 4월...\n",
              "4    계명대 동산병원은 2025년 2월까지 취약계층 암환자 로봇수술비 지원사업을 시행한다...\n",
              "5    가톨릭관동대 국제성모병원은 최근 우즈베키스탄 보건부가 병원을 방문했다고 밝혔다 이번...\n",
              "6    서울대치과병원은 15일부터 23일까지 우즈베키스탄 타슈켄트에서 의료봉사를 마쳤다고 ...\n",
              "7    대한적십자사 서울특별시지사이하 적십자사 서울지사는 오늘25일부터 28일까지 열리는 ...\n",
              "8    고려대안암병원이 보건복지부 및 국립암센터 중앙호스피스센터로부터 소아청소년 완화의료 ...\n",
              "9    서울특별시 서남병원은 최근 열린 제52회 보건의 날 기념식에서 인공관절센터 김영후 ...\n",
              "Name: Content, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "[형태소 분석 및 불용어 처리]\n",
        "\n",
        "\n",
        "*   형태소 기준 토큰화 수행 -> Mecab 사용\n",
        "*   불용어 처리 수행 -> 토큰화 결과 기반 지속적 불용어 업데이트 필요\n"
      ],
      "metadata": {
        "id": "DOTwfOyS_yTa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install konlpy"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bxGdT3hu8Rpf",
        "outputId": "dc416d37-870d-47e0-e8ae-68a5195d92a7"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: konlpy in /usr/local/lib/python3.10/dist-packages (0.6.0)\n",
            "Requirement already satisfied: JPype1>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from konlpy) (1.5.0)\n",
            "Requirement already satisfied: lxml>=4.1.0 in /usr/local/lib/python3.10/dist-packages (from konlpy) (4.9.4)\n",
            "Requirement already satisfied: numpy>=1.6 in /usr/local/lib/python3.10/dist-packages (from konlpy) (1.25.2)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from JPype1>=0.7.0->konlpy) (24.0)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install mecab-python3\n",
        "!pip install unidic-lite # Mecab에 필요한 사전을 설치"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "H25H5gw_9EYp",
        "outputId": "cdac1f99-7f34-4c91-949b-858697b7f679"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: mecab-python3 in /usr/local/lib/python3.10/dist-packages (1.0.9)\n",
            "Requirement already satisfied: unidic-lite in /usr/local/lib/python3.10/dist-packages (1.0.8)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install konlpy       # KoNLPy 라이브러리 설치\n",
        "!apt-get update           # apt-get 업데이트\n",
        "!apt-get install g++ openjdk-8-jdk python-dev python3-dev # 필수 컴포넌트 설치\n",
        "!pip3 install JPype1-py3  # JPype1 설치\n",
        "\n",
        "# Mecab 설치\n",
        "!bash <(curl -s https://raw.githubusercontent.com/konlpy/konlpy/master/scripts/mecab.sh)\n",
        "\n",
        "from konlpy.tag import Mecab\n",
        "mecab = Mecab()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "p6vSUDab91Pp",
        "outputId": "84803404-12e5-4c8e-e284-f3abba6448a1"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: konlpy in /usr/local/lib/python3.10/dist-packages (0.6.0)\n",
            "Requirement already satisfied: JPype1>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from konlpy) (1.5.0)\n",
            "Requirement already satisfied: lxml>=4.1.0 in /usr/local/lib/python3.10/dist-packages (from konlpy) (4.9.4)\n",
            "Requirement already satisfied: numpy>=1.6 in /usr/local/lib/python3.10/dist-packages (from konlpy) (1.25.2)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from JPype1>=0.7.0->konlpy) (24.0)\n",
            "Hit:1 https://cloud.r-project.org/bin/linux/ubuntu jammy-cran40/ InRelease\n",
            "Hit:2 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64  InRelease\n",
            "Get:3 http://security.ubuntu.com/ubuntu jammy-security InRelease [110 kB]\n",
            "Hit:4 http://archive.ubuntu.com/ubuntu jammy InRelease\n",
            "Get:5 http://archive.ubuntu.com/ubuntu jammy-updates InRelease [119 kB]\n",
            "Hit:6 http://archive.ubuntu.com/ubuntu jammy-backports InRelease\n",
            "Hit:7 https://ppa.launchpadcontent.net/c2d4u.team/c2d4u4.0+/ubuntu jammy InRelease\n",
            "Hit:8 https://ppa.launchpadcontent.net/deadsnakes/ppa/ubuntu jammy InRelease\n",
            "Hit:9 https://ppa.launchpadcontent.net/graphics-drivers/ppa/ubuntu jammy InRelease\n",
            "Hit:10 https://ppa.launchpadcontent.net/ubuntugis/ppa/ubuntu jammy InRelease\n",
            "Fetched 229 kB in 1s (168 kB/s)\n",
            "Reading package lists... Done\n",
            "Reading package lists... Done\n",
            "Building dependency tree... Done\n",
            "Reading state information... Done\n",
            "Package python-dev is not available, but is referred to by another package.\n",
            "This may mean that the package is missing, has been obsoleted, or\n",
            "is only available from another source\n",
            "However the following packages replace it:\n",
            "  python2-dev python2 python-dev-is-python3\n",
            "\n",
            "E: Package 'python-dev' has no installation candidate\n",
            "Requirement already satisfied: JPype1-py3 in /usr/local/lib/python3.10/dist-packages (0.5.5.4)\n",
            "mecab-ko is already installed\n",
            "mecab-ko-dic is already installed\n",
            "mecab-python is already installed\n",
            "Done.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "stopwords = ['경향신문','헬스경향','기자','는데','가','등','들','파이낸셜','저작','등','뉴스', '에','는','은','을','했','에게','있','이','의','하','한','다','과','때문','할','수','무단','따른','및','금지','전재']"
      ],
      "metadata": {
        "id": "T6V0oHnABOIZ"
      },
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#토큰화 및 불용어 제거 수행 함수\n",
        "def preprocessing(data):\n",
        "  text_data = []\n",
        "\n",
        "  for sentence in data:\n",
        "    temp_data = []\n",
        "    #- 토큰화\n",
        "    temp_data = tokenizer.morphs(sentence)\n",
        "    #- 불용어 제거\n",
        "    temp_data = [word for word in temp_data if not word in stopwords]\n",
        "    text_data.append(temp_data)\n",
        "\n",
        "  text_data = list(map(' '.join, text_data))\n",
        "\n",
        "  return text_data"
      ],
      "metadata": {
        "id": "cgROH70y_h2U"
      },
      "execution_count": 33,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "text_data = preprocessing(df['Content'])\n",
        "print(text_data[1])\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KmPmevPAAdej",
        "outputId": "fb6ff99c-556c-4a9f-ce04-0f9098a4655d"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "가톨릭 대 인천 성모병원 오늘 29 일 이형섭 구정순 부부 병원 발 전기금 3 억 원 기부 다고 밝혔 병원 이형섭 구정순 부부 감사 를 전하 기 위해 기부금 전달식 열 어 감사패 전달 예우 를 표했 전달식 기부자 이형섭 씨 와 홍승모 몬시뇰 인천 성모 병원장 주요 관계자 참석 이형섭 구정순 부부 지나온 세월 지금 까지 아낌없이 도움 주 셨 던 분 계셨 기 오늘 같이 뜻깊 일 도 었 다며 오늘 결혼기념일 맞이해 우리 부부 작 정성 밀알 되 길 바란다고 밝혔 홍승모 몬시뇰 가톨릭 대 인천 성모 병원장 이형섭 구정순 부부 귀중 마음 깊이 새겨 지역 주민 대표 의료 기관 되 겠 다고 말\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "[머신러닝 분류모델 적용]\n",
        "\n",
        "\n",
        "\n",
        "*   나이브베이즈 분류 모델 적용\n",
        "*   train, test set 비율: train 70%, test 30%\n",
        "\n",
        "\n",
        "\n",
        "```\n",
        "# 코드로 형식 지정됨\n",
        "```\n",
        "\n"
      ],
      "metadata": {
        "id": "hgvkIfCBEHQL"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.feature_extraction.text import CountVectorizer\n",
        "from sklearn.feature_extraction.text import TfidfTransformer\n",
        "from sklearn.naive_bayes import MultinomialNB\n",
        "from sklearn import metrics"
      ],
      "metadata": {
        "id": "mouY2lnKEFb8"
      },
      "execution_count": 37,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#train, test data spliting 수행\n",
        "X = df['Content']\n",
        "y = df['Tags']\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, stratify=y, random_state=1)\n",
        "print('training 뉴스 기사 개수 :', len(X_train))\n",
        "print('test 뉴스 기사 개수 : ', len(X_test))\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lxJyPLYRL2du",
        "outputId": "f2b3cab3-f5f0-4a8a-8acc-480f19c23be0"
      },
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "training 뉴스 기사 개수 : 304\n",
            "test 뉴스 기사 개수 :  131\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "k9MET2T_N_O4"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "7aPXH5XROApG"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#- 단어의 수를 카운트하는 사이킷런의 카운트벡터라이저입니다.\n",
        "count_vect = CountVectorizer()\n",
        "X_train_counts = count_vect.fit_transform(X_train)\n",
        "\n",
        "#- 카운트벡터라이저의 결과로부터 TF-IDF 결과를 얻습니다.\n",
        "tfidf_transformer = TfidfTransformer()\n",
        "X_train_tfidf = tfidf_transformer.fit_transform(X_train_counts)\n",
        "\n",
        "#- 나이브 베이즈 분류기를 수행합니다.\n",
        "#- X_train은 TF-IDF 벡터, y_train은 레이블입니다.\n",
        "clf = MultinomialNB().fit(X_train_tfidf, y_train)\n"
      ],
      "metadata": {
        "id": "bOzfA600NEf0"
      },
      "execution_count": 60,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def tfidf_vectorizer(data):\n",
        "  data_counts = count_vect.transform(data)\n",
        "  data_tfidf = tfidf_transformer.transform(data_counts)\n",
        "  return data_tfidf"
      ],
      "metadata": {
        "id": "f5MYor6pNwd3"
      },
      "execution_count": 61,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred = clf.predict(tfidf_vectorizer(X_test))\n",
        "print(metrics.classification_report(y_test, y_pred))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "c6iUfsG7NkHq",
        "outputId": "3a1d3d85-fe94-4edf-f441-ca23bca87901"
      },
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "          기획       0.95      0.99      0.97        76\n",
            "          보도       1.00      0.95      0.98        64\n",
            "       스트레이트       0.96      0.96      0.96        78\n",
            "\n",
            "    accuracy                           0.97       218\n",
            "   macro avg       0.97      0.97      0.97       218\n",
            "weighted avg       0.97      0.97      0.97       218\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#분류 제대로 하는지 테스트(기사 아무거나 긁어와서 레이블 제대로 추측하는가?)\n",
        "new_sent = preprocessing([\"3명의 소중한 생명이 2023년 계묘년의 힘찬 시작을 알렸다. 차 의과대학교 일산 차병원은 1월 1일 0시 정각에 아기 3명이 동시에 탄생했다고 전했다. ▲엄마 김현정씨(40세) 아빠 장동규씨(42) 사이에서 태어난 쌍둥이 여아 짱순이(태명), 남아 짱짱이(태명)와 ▲엄마 손은서씨(30세)와 아빠 김정섭씨(39세) 사이에서 태어난 여아 복동이(태명)다. 특히 올해는 코로나19 이후 3년 만에 처음으로 가족들과 아기의 대면 만남이 이뤄져 더욱 의미가 컸다는 전언이다. 짱짱이·짱순이 엄마 김현정 씨는 “기다렸던 아이들이 건강하게 태어나서 너무 대견하고 기쁘다”며 “아이 아빠는 안타깝게도 코로나19로 오지 못했지만 새해 첫날 많은 사람의 축복 속에서 태어난 우리 쌍둥이들이 건강하고 밝게 자랐으면 한다”고 소감을 말했다. 쌍둥이의 탄생을 지켜본 할머니 정윤자 씨는 “우리 며느리 현정이에게 고생했다고 말해주고 싶고 쌍둥이가 건강하게 자라기를 바란다”고 말했다. 복동이 아빠 김정섭 씨는 “아이가 태어나서 너무 감격스럽고 건강하게 잘 자라기만을 바란다”고 말했다. 일산차병원 산부인과 김의혁 주치의는 “저출산이 심해지는 상황에서 대면으로 소중하고 귀한 아기 탄생을 함께할 수 있어 기쁘다”며 “첫 아기의 탄생과 함께 출산의 기쁨과 생명의 소중함을 새해 첫날 다시 한번 상기하는 시간이 되기를 바란다”고 말했다.\"])\n",
        "print(clf.predict(tfidf_vectorizer(new_sent)))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "09pmYNVyPAmB",
        "outputId": "40cd8ff9-9865-4929-f7ac-8705a8fad7e5"
      },
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['스트레이트']\n"
          ]
        }
      ]
    }
  ]
}