3_簡單貝葉斯分類器(Naive Bayes classifier).ipynb

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   "cell_type": "code",
   "execution_count": 1,
   "id": "a5668eb0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import jieba\n",
    "import numpy as np\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "from sklearn.naive_bayes import MultinomialNB\n",
    "from sklearn.metrics import accuracy_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5a74c2fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 繁體中文範例句子\n",
    "documents = [\n",
    "    \"他的速度真快\",\n",
    "    \"他的速度真慢\",\n",
    "    \"這是一個句子\",\n",
    "    \"這是另一個句子\",\n",
    "    \"這個數字是五\",\n",
    "    \"這個數字不是五\",\n",
    "    \"他的身高很高\",\n",
    "    \"他的身高不高\",\n",
    "    \"他的身高很矮\",\n",
    "    \"他的身高不矮\",\n",
    "    \"今天天氣很好\",\n",
    "    \"今天天氣不好\",\n",
    "    \"這個測試真難\",\n",
    "    \"這個測試不難\",\n",
    "    \"這是一個好例子\",\n",
    "    \"這不是一個好例子\",\n",
    "    \"這是一個壞例子\",\n",
    "    \"這不是一個壞例子\",\n",
    "    \"他是我最好的朋友\",\n",
    "    \"他不是我最好的朋友\",\n",
    "    \"他是我最壞的朋友\",\n",
    "    \"他不是我最壞的朋友\",\n",
    "    \"我長得好笑\",\n",
    "    \"我長得不好笑\"\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "57014e0e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 為每個句子隨機生成標籤\n",
    "labels = [1,0,1,0,1,0,1,0,1,0,1,0,1,0,1,0,1,0,1,0,1,0,1,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "054af9c0",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Building prefix dict from the default dictionary ...\n",
      "Loading model from cache C:\\Users\\darren\\AppData\\Local\\Temp\\jieba.cache\n",
      "Loading model cost 0.581 seconds.\n",
      "Prefix dict has been built successfully.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "['他 的 速度 真 快',\n",
       " '他 的 速度 真慢',\n",
       " '這是 一個 句子',\n",
       " '這是 另 一個 句子',\n",
       " '這個 數字 是 五',\n",
       " '這個 數字 不是 五',\n",
       " '他 的 身高 很 高',\n",
       " '他 的 身高 不高',\n",
       " '他 的 身高 很矮',\n",
       " '他 的 身高 不 矮',\n",
       " '今天 天氣 很 好',\n",
       " '今天 天氣 不好',\n",
       " '這個 測試 真難',\n",
       " '這個 測試 不難',\n",
       " '這是 一個 好 例子',\n",
       " '這 不是 一個 好 例子',\n",
       " '這是 一個 壞 例子',\n",
       " '這 不是 一個 壞 例子',\n",
       " '他 是 我 最好 的 朋友',\n",
       " '他 不是 我 最好 的 朋友',\n",
       " '他 是 我 最壞 的 朋友',\n",
       " '他 不是 我 最壞 的 朋友',\n",
       " '我長 得 好笑',\n",
       " '我長 得 不好 笑']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 分詞\n",
    "jieba.add_word('不')\n",
    "documents = [' '.join(jieba.cut(doc)) for doc in documents]; documents"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9b0a5516",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 切分數據集為訓練集和測試集\n",
    "X_train, X_test, y_train, y_test = train_test_split(documents, labels, test_size=0.5, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0a47fa86",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 建立 TF-IDF 物件\n",
    "vectorizer = TfidfVectorizer()\n",
    "\n",
    "# 對訓練集進行 TF-IDF 轉換\n",
    "X_train_transformed = vectorizer.fit_transform(X_train)\n",
    "\n",
    "# 轉換測試集\n",
    "X_test_transformed = vectorizer.transform(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "36b9082f",
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "MultinomialNB()"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 建立貝葉斯分類器物件\n",
    "clf = MultinomialNB()\n",
    "\n",
    "# 訓練模型\n",
    "clf.fit(X_train_transformed, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3b9b6a99",
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     "text": [
      "['他 的 身高 很矮', '這是 一個 壞 例子', '他 的 速度 真 快', '他 是 我 最好 的 朋友', '今天 天氣 不好', '他 的 身高 不 矮', '這個 測試 不難', '他 的 速度 真慢', '他 不是 我 最壞 的 朋友', '這個 數字 不是 五', '這是 一個 句子', '這個 測試 真難']\n",
      "[1 0 0 0 1 1 1 0 0 1 0 1]\n"
     ]
    }
   ],
   "source": [
    "# 進行預測\n",
    "y_pred = clf.predict(X_test_transformed)\n",
    "\n",
    "# 輸出預測結果\n",
    "print(X_test)\n",
    "print(y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4ac30ae0",
   "metadata": {},
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    {
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       "0.3333333333333333"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accuracy_score(y_test, y_pred)"
   ]
  }
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