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xccds/word2vec.ipynb

Created December 28, 2014 03:56
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word2vec.ipynb
{
"metadata": {
"name": "",
"signature": "sha256:133d27327505f16b3c5f501baccc320cb1fbc3118bbbecb9020dc79b35b889b4"
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"nbformat": 3,
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"worksheets": [
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- \u5c1d\u8bd5\u4e86jieba\u5305\u6765\u5bf9\u8bc4\u8bba\u8fdb\u884c\u5206\u8bcd\n",
"- \u518d\u4f7f\u7528simgen\u5305\u7684word2vec\u51fd\u6570\u83b7\u53d6\u8bcd\u5411\u91cf\n",
"- \u6839\u636e\u8bcd\u5411\u91cf\u548c\u8bcd\u7684\u76f8\u4f3c\u6027\uff0c\u68c0\u7d22\u540c\u4e49\u8bcd"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# \u5c06\u8bc4\u8bba\u4ece\u6570\u636e\u5e93\u8bfb\u5165\n",
"from sqlalchemy import create_engine\n",
"engine = create_engine('oracle://user:password@bi_data')\n",
"import pandas as pd\n",
"df = pd.read_sql_query(str_sql, engine)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df.shape"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 25,
"text": [
"(16710481, 8)"
]
}
],
"prompt_number": 25
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df.head()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>cmmnt_date</th>\n",
" <th>ordr_id</th>\n",
" <th>end_user_id</th>\n",
" <th>prod_name</th>\n",
" <th>prod_id</th>\n",
" <th>rate</th>\n",
" <th>good_cntnt</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2014-08-10</td>\n",
" <td> 4.023944e+11</td>\n",
" <td> 5817243</td>\n",
" <td> HSTYLE/\u97e9\u90fd\u8863\u820d \u7c73\u59ae\u54c8\u9c812014\u590f\u88c5\u65b0\u6b3e\u5973\u7ae5\u88c5\u97e9\u7248\u5361\u901a\u56fe\u6848\u767e\u8936\u77ed\u88d9ZD3033\u2461\u73ab\u7ea2...</td>\n",
" <td> 22888729</td>\n",
" <td> 5</td>\n",
" <td> \u6027\u4ef7\u6bd4\u9ad8\uff0c\u5c0f\u670b\u53cb\u559c\u6b22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2014-07-09</td>\n",
" <td> 2.451833e+08</td>\n",
" <td> 12550004</td>\n",
" <td> HSTYLE/\u97e9\u90fd\u8863\u820d \u7c73\u59ae\u54c8\u9c812014\u590f\u88c5\u65b0\u6b3e\u5973\u7ae5\u88c5\u97e9\u7248\u5361\u901a\u56fe\u6848\u767e\u8936\u77ed\u88d9ZD3033\u2461\u73ab\u7ea2...</td>\n",
" <td> 22888729</td>\n",
" <td> 5</td>\n",
" <td> \u8863\u670d\u6bcf\u4ef6\u90fd\u597d\uff0c\u670d\u52a1\u66f4\u597d\uff0c\u5173\u6ce8\u4f60\u4eec\uff0c\u4e0b\u6b21\u518d\u6765\uff01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2014-09-22</td>\n",
" <td> 8.691191e+11</td>\n",
" <td> 123415597</td>\n",
" <td> Maihu/\u9ea6\u72d0 \u65e5\u672c\u8fdb\u53e3 inomata \u5851\u6599\u5236\u51b0\u683c \u5236\u51b0\u5668 \u5236\u51b0\u6a21\u5177 \u51b0\u683c \u5236\u51b0\u76d2\u5e26\u76d6\u51b0...</td>\n",
" <td> 17588803</td>\n",
" <td> 5</td>\n",
" <td> \u5bf9\u5546\u54c1\u975e\u5e38\u6ee1\u610f</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2014-10-21</td>\n",
" <td> 1.269396e+12</td>\n",
" <td> 139399779</td>\n",
" <td> \u97e9\u8863\u515c 2014\u79cb\u51ac\u65b0\u6b3e\u97e9\u7248\u5973\u88c5\u65f6\u5c1a\u4fee\u8eab\u82b1\u6735\u62fc\u63a5\u68d2\u7403\u670d\u5f00\u886b\u77ed\u5916\u5957 X8833\u6df1\u84dd\u8272L</td>\n",
" <td> 33678751</td>\n",
" <td> 5</td>\n",
" <td> \u5b9d\u8d1d\u6536\u5230\uff0c\u592a\u559c\u6b22\u4e86\u5927\u5c0f\u521a\u597d\u5f88\u5408\u8eab\uff0c\u505a\u5de5\u7cbe\u7ec6\u6ca1\u6709\u7455\u75b5\uff0c\u4ee5\u540e\u6709\u9700\u8981\u8fd8\u4f1a\u518d\u6765\u7684\uff01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2014-11-24</td>\n",
" <td> 1.348798e+12</td>\n",
" <td> 130075686</td>\n",
" <td> \u8d1d\u4e1d\u6d01BEISIJIE \u7cbe\u81f4\u82b1\u8fb9\u6bdb\u5dfe34*76 5845210\u84dd\u827234*76cm</td>\n",
" <td> 17591645</td>\n",
" <td> 5</td>\n",
" <td> \u4e0d\u9519\uff0c\u4fbf\u5b9c</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 7,
"text": [
" cmmnt_date ordr_id end_user_id \\\n",
"0 2014-08-10 4.023944e+11 5817243 \n",
"1 2014-07-09 2.451833e+08 12550004 \n",
"2 2014-09-22 8.691191e+11 123415597 \n",
"3 2014-10-21 1.269396e+12 139399779 \n",
"4 2014-11-24 1.348798e+12 130075686 \n",
"\n",
" prod_name prod_id rate \\\n",
"0 HSTYLE/\u97e9\u90fd\u8863\u820d \u7c73\u59ae\u54c8\u9c812014\u590f\u88c5\u65b0\u6b3e\u5973\u7ae5\u88c5\u97e9\u7248\u5361\u901a\u56fe\u6848\u767e\u8936\u77ed\u88d9ZD3033\u2461\u73ab\u7ea2... 22888729 5 \n",
"1 HSTYLE/\u97e9\u90fd\u8863\u820d \u7c73\u59ae\u54c8\u9c812014\u590f\u88c5\u65b0\u6b3e\u5973\u7ae5\u88c5\u97e9\u7248\u5361\u901a\u56fe\u6848\u767e\u8936\u77ed\u88d9ZD3033\u2461\u73ab\u7ea2... 22888729 5 \n",
"2 Maihu/\u9ea6\u72d0 \u65e5\u672c\u8fdb\u53e3 inomata \u5851\u6599\u5236\u51b0\u683c \u5236\u51b0\u5668 \u5236\u51b0\u6a21\u5177 \u51b0\u683c \u5236\u51b0\u76d2\u5e26\u76d6\u51b0... 17588803 5 \n",
"3 \u97e9\u8863\u515c 2014\u79cb\u51ac\u65b0\u6b3e\u97e9\u7248\u5973\u88c5\u65f6\u5c1a\u4fee\u8eab\u82b1\u6735\u62fc\u63a5\u68d2\u7403\u670d\u5f00\u886b\u77ed\u5916\u5957 X8833\u6df1\u84dd\u8272L 33678751 5 \n",
"4 \u8d1d\u4e1d\u6d01BEISIJIE \u7cbe\u81f4\u82b1\u8fb9\u6bdb\u5dfe34*76 5845210\u84dd\u827234*76cm 17591645 5 \n",
"\n",
" good_cntnt \n",
"0 \u6027\u4ef7\u6bd4\u9ad8\uff0c\u5c0f\u670b\u53cb\u559c\u6b22 \n",
"1 \u8863\u670d\u6bcf\u4ef6\u90fd\u597d\uff0c\u670d\u52a1\u66f4\u597d\uff0c\u5173\u6ce8\u4f60\u4eec\uff0c\u4e0b\u6b21\u518d\u6765\uff01 \n",
"2 \u5bf9\u5546\u54c1\u975e\u5e38\u6ee1\u610f \n",
"3 \u5b9d\u8d1d\u6536\u5230\uff0c\u592a\u559c\u6b22\u4e86\u5927\u5c0f\u521a\u597d\u5f88\u5408\u8eab\uff0c\u505a\u5de5\u7cbe\u7ec6\u6ca1\u6709\u7455\u75b5\uff0c\u4ee5\u540e\u6709\u9700\u8981\u8fd8\u4f1a\u518d\u6765\u7684\uff01 \n",
"4 \u4e0d\u9519\uff0c\u4fbf\u5b9c "
]
}
],
"prompt_number": 7
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- \u4f7f\u7528\u7ed3\u5df4\u5206\u8bcd"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import jieba\n",
"def cutword(x):\n",
" if isinstance(x, str): x = x.decode('utf8') # \u89e3\u7801\u4e3aunicode \n",
" x = unicode(x) #\u5c06\u6570\u5b57\u53d8\u5b57\u7b26\n",
" seg = jieba.cut(x)\n",
" return ' '.join(seg)\n",
"# cutword(string)"
],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- \u5904\u7406\u4e2d\u6587\u65f6\u7684\u6ce8\u610f\u9879\uff0c\u9700\u8981\u5c06\u5916\u90e8\u8f93\u5165\u7684\u4e2d\u6587\u5b57\u7b26\u89e3\u7801\u4e3aunicode\n",
"- \u518d\u8f93\u51fa\u5230\u5916\u90e8\u6587\u6863\u65f6\uff0c\u9700\u518d\u4eceunicode\u7f16\u7801\n",
"- \u53c2\u8003\u6587\u6863\uff1ahttp://python.jobbole.com/80831/"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"x = '\u4e2d\u56fd' #\u5916\u90e8\u8f93\u5165\n",
"y = x.decode('utf8') #\u89e3\u7801\u4e3aunicode \u5728python\u5185\u90e8\u5904\u7406\n",
"z = y.encode('utf8') #\u7f16\u7801\u4e3astr \u518d\u8f93\u51fa "
],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- \u5c06\u6240\u6709\u8bc4\u8bba\u8fdb\u884c\u5206\u8bcd"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"df['seg_word'] = df.good_cntnt.map(cutword)\n",
"df.head()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>cmmnt_date</th>\n",
" <th>ordr_id</th>\n",
" <th>end_user_id</th>\n",
" <th>prod_name</th>\n",
" <th>prod_id</th>\n",
" <th>rate</th>\n",
" <th>good_cntnt</th>\n",
" <th>seg_word</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2014-08-10</td>\n",
" <td> 4.023944e+11</td>\n",
" <td> 5817243</td>\n",
" <td> HSTYLE/\u97e9\u90fd\u8863\u820d \u7c73\u59ae\u54c8\u9c812014\u590f\u88c5\u65b0\u6b3e\u5973\u7ae5\u88c5\u97e9\u7248\u5361\u901a\u56fe\u6848\u767e\u8936\u77ed\u88d9ZD3033\u2461\u73ab\u7ea2...</td>\n",
" <td> 22888729</td>\n",
" <td> 5</td>\n",
" <td> \u6027\u4ef7\u6bd4\u9ad8\uff0c\u5c0f\u670b\u53cb\u559c\u6b22</td>\n",
" <td> \u6027\u4ef7\u6bd4 \u9ad8 \uff0c \u5c0f\u670b\u53cb \u559c\u6b22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2014-07-09</td>\n",
" <td> 2.451833e+08</td>\n",
" <td> 12550004</td>\n",
" <td> HSTYLE/\u97e9\u90fd\u8863\u820d \u7c73\u59ae\u54c8\u9c812014\u590f\u88c5\u65b0\u6b3e\u5973\u7ae5\u88c5\u97e9\u7248\u5361\u901a\u56fe\u6848\u767e\u8936\u77ed\u88d9ZD3033\u2461\u73ab\u7ea2...</td>\n",
" <td> 22888729</td>\n",
" <td> 5</td>\n",
" <td> \u8863\u670d\u6bcf\u4ef6\u90fd\u597d\uff0c\u670d\u52a1\u66f4\u597d\uff0c\u5173\u6ce8\u4f60\u4eec\uff0c\u4e0b\u6b21\u518d\u6765\uff01</td>\n",
" <td> \u8863\u670d \u6bcf\u4ef6 \u90fd \u597d \uff0c \u670d\u52a1 \u66f4\u597d \uff0c \u5173\u6ce8 \u4f60\u4eec \uff0c \u4e0b\u6b21 \u518d \u6765 \uff01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2014-09-22</td>\n",
" <td> 8.691191e+11</td>\n",
" <td> 123415597</td>\n",
" <td> Maihu/\u9ea6\u72d0 \u65e5\u672c\u8fdb\u53e3 inomata \u5851\u6599\u5236\u51b0\u683c \u5236\u51b0\u5668 \u5236\u51b0\u6a21\u5177 \u51b0\u683c \u5236\u51b0\u76d2\u5e26\u76d6\u51b0...</td>\n",
" <td> 17588803</td>\n",
" <td> 5</td>\n",
" <td> \u5bf9\u5546\u54c1\u975e\u5e38\u6ee1\u610f</td>\n",
" <td> \u5bf9 \u5546\u54c1 \u975e\u5e38 \u6ee1\u610f</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2014-10-21</td>\n",
" <td> 1.269396e+12</td>\n",
" <td> 139399779</td>\n",
" <td> \u97e9\u8863\u515c 2014\u79cb\u51ac\u65b0\u6b3e\u97e9\u7248\u5973\u88c5\u65f6\u5c1a\u4fee\u8eab\u82b1\u6735\u62fc\u63a5\u68d2\u7403\u670d\u5f00\u886b\u77ed\u5916\u5957 X8833\u6df1\u84dd\u8272L</td>\n",
" <td> 33678751</td>\n",
" <td> 5</td>\n",
" <td> \u5b9d\u8d1d\u6536\u5230\uff0c\u592a\u559c\u6b22\u4e86\u5927\u5c0f\u521a\u597d\u5f88\u5408\u8eab\uff0c\u505a\u5de5\u7cbe\u7ec6\u6ca1\u6709\u7455\u75b5\uff0c\u4ee5\u540e\u6709\u9700\u8981\u8fd8\u4f1a\u518d\u6765\u7684\uff01</td>\n",
" <td> \u5b9d\u8d1d \u6536\u5230 \uff0c \u592a \u559c\u6b22 \u4e86 \u5927\u5c0f \u521a\u597d \u5f88 \u5408\u8eab \uff0c \u505a\u5de5 \u7cbe\u7ec6 \u6ca1\u6709 \u7455\u75b5 \uff0c \u4ee5\u540e \u6709...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2014-11-24</td>\n",
" <td> 1.348798e+12</td>\n",
" <td> 130075686</td>\n",
" <td> \u8d1d\u4e1d\u6d01BEISIJIE \u7cbe\u81f4\u82b1\u8fb9\u6bdb\u5dfe34*76 5845210\u84dd\u827234*76cm</td>\n",
" <td> 17591645</td>\n",
" <td> 5</td>\n",
" <td> \u4e0d\u9519\uff0c\u4fbf\u5b9c</td>\n",
" <td> \u4e0d\u9519 \uff0c \u4fbf\u5b9c</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 12,
"text": [
" cmmnt_date ordr_id end_user_id \\\n",
"0 2014-08-10 4.023944e+11 5817243 \n",
"1 2014-07-09 2.451833e+08 12550004 \n",
"2 2014-09-22 8.691191e+11 123415597 \n",
"3 2014-10-21 1.269396e+12 139399779 \n",
"4 2014-11-24 1.348798e+12 130075686 \n",
"\n",
" prod_name prod_id rate \\\n",
"0 HSTYLE/\u97e9\u90fd\u8863\u820d \u7c73\u59ae\u54c8\u9c812014\u590f\u88c5\u65b0\u6b3e\u5973\u7ae5\u88c5\u97e9\u7248\u5361\u901a\u56fe\u6848\u767e\u8936\u77ed\u88d9ZD3033\u2461\u73ab\u7ea2... 22888729 5 \n",
"1 HSTYLE/\u97e9\u90fd\u8863\u820d \u7c73\u59ae\u54c8\u9c812014\u590f\u88c5\u65b0\u6b3e\u5973\u7ae5\u88c5\u97e9\u7248\u5361\u901a\u56fe\u6848\u767e\u8936\u77ed\u88d9ZD3033\u2461\u73ab\u7ea2... 22888729 5 \n",
"2 Maihu/\u9ea6\u72d0 \u65e5\u672c\u8fdb\u53e3 inomata \u5851\u6599\u5236\u51b0\u683c \u5236\u51b0\u5668 \u5236\u51b0\u6a21\u5177 \u51b0\u683c \u5236\u51b0\u76d2\u5e26\u76d6\u51b0... 17588803 5 \n",
"3 \u97e9\u8863\u515c 2014\u79cb\u51ac\u65b0\u6b3e\u97e9\u7248\u5973\u88c5\u65f6\u5c1a\u4fee\u8eab\u82b1\u6735\u62fc\u63a5\u68d2\u7403\u670d\u5f00\u886b\u77ed\u5916\u5957 X8833\u6df1\u84dd\u8272L 33678751 5 \n",
"4 \u8d1d\u4e1d\u6d01BEISIJIE \u7cbe\u81f4\u82b1\u8fb9\u6bdb\u5dfe34*76 5845210\u84dd\u827234*76cm 17591645 5 \n",
"\n",
" good_cntnt \\\n",
"0 \u6027\u4ef7\u6bd4\u9ad8\uff0c\u5c0f\u670b\u53cb\u559c\u6b22 \n",
"1 \u8863\u670d\u6bcf\u4ef6\u90fd\u597d\uff0c\u670d\u52a1\u66f4\u597d\uff0c\u5173\u6ce8\u4f60\u4eec\uff0c\u4e0b\u6b21\u518d\u6765\uff01 \n",
"2 \u5bf9\u5546\u54c1\u975e\u5e38\u6ee1\u610f \n",
"3 \u5b9d\u8d1d\u6536\u5230\uff0c\u592a\u559c\u6b22\u4e86\u5927\u5c0f\u521a\u597d\u5f88\u5408\u8eab\uff0c\u505a\u5de5\u7cbe\u7ec6\u6ca1\u6709\u7455\u75b5\uff0c\u4ee5\u540e\u6709\u9700\u8981\u8fd8\u4f1a\u518d\u6765\u7684\uff01 \n",
"4 \u4e0d\u9519\uff0c\u4fbf\u5b9c \n",
"\n",
" seg_word \n",
"0 \u6027\u4ef7\u6bd4 \u9ad8 \uff0c \u5c0f\u670b\u53cb \u559c\u6b22 \n",
"1 \u8863\u670d \u6bcf\u4ef6 \u90fd \u597d \uff0c \u670d\u52a1 \u66f4\u597d \uff0c \u5173\u6ce8 \u4f60\u4eec \uff0c \u4e0b\u6b21 \u518d \u6765 \uff01 \n",
"2 \u5bf9 \u5546\u54c1 \u975e\u5e38 \u6ee1\u610f \n",
"3 \u5b9d\u8d1d \u6536\u5230 \uff0c \u592a \u559c\u6b22 \u4e86 \u5927\u5c0f \u521a\u597d \u5f88 \u5408\u8eab \uff0c \u505a\u5de5 \u7cbe\u7ec6 \u6ca1\u6709 \u7455\u75b5 \uff0c \u4ee5\u540e \u6709... \n",
"4 \u4e0d\u9519 \uff0c \u4fbf\u5b9c "
]
}
],
"prompt_number": 12
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- \u5c06\u5206\u8bcd\u540e\u7684\u8bc4\u8bba\u53d8\u6210\u5217\u8868\n",
"- \u4f7f\u7528gensim\u5305\u4e2d\u7684word2vec\u8fdb\u884c\u8bad\u7ec3\uff0c\u83b7\u5f97\u8bcd\u5411\u91cf"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"txt = df['seg_word'].values\n",
"txtlist = []\n",
"for x in txt:\n",
" txtlist.append(x.split())\n",
"\n",
"import logging\n",
"logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s',level=logging.INFO)\n",
"\n",
"num_features = 300\n",
"min_word_count = 10\n",
"num_workers = 4\n",
"context = 10\n",
"downsampling = 1e-3\n",
"\n",
"from gensim.models import word2vec\n",
"print \"traing model...\"\n",
"model = word2vec.Word2Vec(txtlist, workers = num_workers, size= num_features, min_count=min_word_count, window = context, sample = downsampling)\n",
"model.init_sims(replace=True)\n",
"model_name = 'allcomword2vec'\n",
"model.save(model_name)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"traing model...\n"
]
}
],
"prompt_number": 13
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- \u5c1d\u8bd5\u68c0\u7d22\u67d0\u4e2a\u8bcd\u7684\u540c\u4e49\u8bcd"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"for word, word_simi in model.most_similar(u'\u4e30\u6ee1', topn=20):\n",
" print word, word_simi"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"\u80f8\u90e8 0.728694856167\n",
"\u589e\u5927 0.708100199699\n",
"\u8089\u8089 0.694790780544\n",
"\u53d8\u5927 0.641858637333\n",
"\u575a\u633a 0.640198707581\n",
"\u4e0b\u5782 0.606641292572\n",
"\u633a\u8d77\u6765 0.606020510197\n",
"\u5347\u676f 0.602514088154\n",
"\u80f8\u578b 0.595118582249\n",
"\u7f69\u676f 0.593821108341\n",
"\u5916\u6269 0.593108892441\n",
"\u677e\u5f1b 0.578672170639\n",
"\u7d27\u81f4 0.572979569435\n",
"\u7d27\u5b9e 0.571806252003\n",
"\u5723\u8377 0.568730592728\n",
"\u8d8a\u53d8 0.562036752701\n",
"\u6491\u6ee1 0.558072209358\n",
"\u633a\u62d4 0.556601524353\n",
"\u8089\u611f 0.556496024132\n",
"\u80f8 0.552304565907\n"
]
}
],
"prompt_number": 26
}
],
"metadata": {}
}
]
}
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