diff --git "a/AI/\354\202\254\354\240\204 \354\203\235\354\204\261.ipynb" "b/AI/\354\202\254\354\240\204 \354\203\235\354\204\261.ipynb" index 241d1a0..21483f0 100644 --- "a/AI/\354\202\254\354\240\204 \354\203\235\354\204\261.ipynb" +++ "b/AI/\354\202\254\354\240\204 \354\203\235\354\204\261.ipynb" @@ -14912,11 +14912,178 @@ "standard_okt_data" ] }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# 방언 문장의 길이와 그 길이에 해당되는 문장의 수\n", + "import matplotlib\n", + "import matplotlib.pyplot as plt\n", + "\n", + "plt.hist([len(sentence) for sentence in dialect_okt_data], bins=10)\n", + "plt.xlabel('length of dialect')\n", + "plt.ylabel('number of dialect')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# 표준어 문장의 길이와 그 길이에 해당되는 문장의 수\n", + "\n", + "plt.hist([len(sentence) for sentence in standard_okt_data], bins=10)\n", + "plt.xlabel('length of standard')\n", + "plt.ylabel('number of standard')\n", + "plt.show()" + ] + }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], + "source": [ + "# 최대 길이로 모든 문장의 길이를 패딩하면 규모가 너무 커짐\n", + "### 함수 선언\n", + "def threshold_len_80(max_len, data):\n", + " sentence_count=0\n", + " for sentence in data:\n", + " if(len(sentence) <= max_len):\n", + " sentence_count += 1\n", + " return sentence_count/len(data)*100" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "dialect 중 50 이하인 비율은 94.61238466660326\n", + "standard 중 50 이하인 비율은 94.85915397263253\n" + ] + } + ], + "source": [ + "dialect_max_len = 50\n", + "dialect_ratio = threshold_len_80(dialect_max_len, dialect_okt_data)\n", + "\n", + "standard_max_len = 50\n", + "standard_ratio = threshold_len_80(standard_max_len, standard_okt_data)\n", + "\n", + "print(f\"dialect 중 {dialect_max_len} 이하인 비율은 {dialect_ratio}\")\n", + "print(f\"standard 중 {standard_max_len} 이하인 비율은 {standard_ratio}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "filtered_standard_data = []\n", + "for text in standard_okt_data:\n", + " if len(text) < 50:\n", + " filtered_standard_data.append(text)\n", + " else:\n", + " pass " + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "filtered_dialect_data = []\n", + "for text in dialect_okt_data:\n", + " if len(text) < 50:\n", + " filtered_dialect_data.append(text)\n", + " else:\n", + " pass " + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.hist([len(sentence) for sentence in filtered_standard_data], bins=10)\n", + "plt.xlabel('length of standard')\n", + "plt.ylabel('number of standard')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.hist([len(sentence) for sentence in filtered_dialect_data], bins=10)\n", + "plt.xlabel('length of dialect')\n", + "plt.ylabel('number of dialect')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], "source": [ "from gensim.models import Word2Vec\n", "import matplotlib.pyplot as plt" @@ -14924,12 +15091,12 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ - "dialect_word2vec = Word2Vec(sentences=dialect_okt_data, vector_size=100, min_count=1, window=5, workers=4)\n", - "standard_word2vec = Word2Vec(sentences=standard_okt_data, vector_size=100, min_count=1, window=5, workers=4)\n", + "dialect_word2vec = Word2Vec(sentences=filtered_dialect_data, vector_size=100, min_count=1, window=5, workers=4)\n", + "standard_word2vec = Word2Vec(sentences=filtered_standard_data, vector_size=100, min_count=1, window=5, workers=4)\n", "\n", "dialect_word2vec.save(\"dialect_word2vec.bin\")\n", "standard_word2vec.save(\"standard_word2vec.bin\")"