{"id":15996,"date":"2023-10-20T07:23:04","date_gmt":"2023-10-19T23:23:04","guid":{"rendered":"http:\/\/www.biocloudservice.com\/wordpress\/?p=15996"},"modified":"2023-10-20T15:24:01","modified_gmt":"2023-10-20T07:24:01","slug":"0879b3ff57","status":"publish","type":"post","link":"http:\/\/www.biocloudservice.com\/wordpress\/?p=15996","title":{"rendered":"\u751f\u4fe1\u5927\u6740\u5668\u4e4b\u795e\u5947\u7684\u8d1d\u53f6\u65af\u7f51\u7edc(4)"},"content":{"rendered":"<section style=\"font-size: 16px;\">\n<p style=\"text-align: center;\"><img decoding=\"async\" class=\"rich_pages wxw-img\" data-galleryid=\"\" data-ratio=\"0.3888888888888889\" data-s=\"300,640\" data-src=\"https:\/\/i0.wp.com\/www.biocloudservice.com\/wordpress\/wp-content\/uploads\/2023\/10\/41697786587-1.jpg?w=640\" data-type=\"jpeg\" data-w=\"1080\" src=\"https:\/\/i0.wp.com\/www.biocloudservice.com\/wordpress\/wp-content\/uploads\/2023\/10\/41697786587-1.jpg?w=640\" data-recalc-dims=\"1\"><\/p>\n<p style=\"text-indent: 2em;text-wrap: wrap;\" powered-by=\"xiumi.us\"><span style=\"font-family: mp-quote, -apple-system-font, BlinkMacSystemFont, &quot;Helvetica Neue&quot;, &quot;PingFang SC&quot;, &quot;Hiragino Sans GB&quot;, &quot;Microsoft YaHei UI&quot;, &quot;Microsoft YaHei&quot;, Arial, sans-serif;text-indent: 2em;letter-spacing: 0.034em;\">\u5927\u5bb6\u597d\uff0c\u5c0f\u5e08\u59b9\u53c8\u548c\u5927\u5bb6\u89c1\u9762\u5566\u3002<\/span><span style=\"font-family: mp-quote, -apple-system-font, BlinkMacSystemFont, &quot;Helvetica Neue&quot;, &quot;PingFang SC&quot;, &quot;Hiragino Sans GB&quot;, &quot;Microsoft YaHei UI&quot;, &quot;Microsoft YaHei&quot;, Arial, sans-serif;text-indent: 2em;letter-spacing: 0.034em;\">\u5728\u4e86\u89e3\u5b8c\u8d1d\u53f6\u65af\u7f51\u7edc\u76f8\u5173\u7684\u57fa\u7840\u77e5\u8bc6\u540e\uff0c\u540c\u5b66\u4eec\u662f\u4e0d\u662f\u5df2\u7ecf\u8dc3\u8dc3\u6b32\u8bd5\u4e86\uff1f<\/span><span style=\"font-family: mp-quote, -apple-system-font, BlinkMacSystemFont, &quot;Helvetica Neue&quot;, &quot;PingFang SC&quot;, &quot;Hiragino Sans GB&quot;, &quot;Microsoft YaHei UI&quot;, &quot;Microsoft YaHei&quot;, Arial, sans-serif;text-indent: 2em;letter-spacing: 0.034em;\">\u90a3\u4e48\u5c31\u8ba9\u6211\u4eec\u4ece\u4e00\u4e2a\u8f83\u4e3a\u7b80\u5355\u7684\u4f8b\u5b50\u5f00\u59cb\u5427\uff01<\/span>\n<\/p>\n<section powered-by=\"xiumi.us\">\n<p style=\"text-indent: 2em;text-wrap: wrap;text-align: center;\"><span style=\"text-indent: 2em;\"><img decoding=\"async\" class=\"rich_pages wxw-img\" data-cropselx1=\"0\" data-cropselx2=\"84\" data-cropsely1=\"0\" data-cropsely2=\"80\" data-ratio=\"0.9689922480620154\" data-src=\"https:\/\/i0.wp.com\/www.biocloudservice.com\/wordpress\/wp-content\/uploads\/2023\/10\/11697786588.jpg?w=640\" data-type=\"jpeg\" data-w=\"516\" src=\"https:\/\/i0.wp.com\/www.biocloudservice.com\/wordpress\/wp-content\/uploads\/2023\/10\/11697786588.jpg?w=640\" data-recalc-dims=\"1\"><\/span><\/p>\n<p style=\"text-indent: 2em;text-wrap: wrap;\"><span style=\"text-indent: 2em;\"><br \/>\n<\/span><\/p>\n<p style=\"text-indent: 2em;text-wrap: wrap;\">\u5728\u672c\u4f8b\u4e2d\uff0c\u5c0f\u5e08\u59b9\u5c06\u5e26\u5927\u5bb6\u4f7f\u7528R\u8bed\u8a00bnlearn\u5305\u4e2d\u9644\u5e26\u7684learning.test\u6570\u636e\u96c6\uff0c\u8be5\u6570\u636e\u96c6\u662f\u7531\u51716\u4e2a\u4ece\u5c5e\u5206\u7c7b\u5206\u5e03\u7684\u8282\u70b9\u6784\u6210\uff0c\u4e5f\u5c31\u662f\u8bf4\u6bcf\u4e2a\u8282\u70b9\u90fd\u96b6\u5c5e\u4e8e\u4e00\u4e2a\u79bb\u6563\u5206\u5e03:<\/p>\n<\/section>\n<section class=\"code-snippet__fix code-snippet__js\">\n<ul class=\"code-snippet__line-index code-snippet__js\">\n<li><\/li>\n<li><\/li>\n<li><\/li>\n<\/ul>\n<pre class=\"code-snippet__js\" data-lang=\"c\"><code><span class=\"code-snippet_outer\">library(bnlearn) &nbsp;<\/span><\/code><code><span class=\"code-snippet_outer\">data(learning.test) &nbsp;<\/span><\/code><code><span class=\"code-snippet_outer\">summary(learning.test)<\/span><\/code><\/pre>\n<\/section>\n<section style=\"text-align: center;margin-top: 10px;margin-bottom: 10px;line-height: 0;\" powered-by=\"xiumi.us\">\n<section style=\"vertical-align: middle;display: inline-block;line-height: 0;\"><img decoding=\"async\" class=\"rich_pages wxw-img\" data-ratio=\"0.7595744680851064\" data-s=\"300,640\" data-src=\"https:\/\/i0.wp.com\/www.biocloudservice.com\/wordpress\/wp-content\/uploads\/2023\/10\/41697786588.png?w=640\" data-type=\"png\" data-w=\"470\" src=\"https:\/\/i0.wp.com\/www.biocloudservice.com\/wordpress\/wp-content\/uploads\/2023\/10\/41697786588.png?w=640\" data-recalc-dims=\"1\"><\/section>\n<\/section>\n<section powered-by=\"xiumi.us\">\n<p style=\"text-wrap: wrap;\"><span style=\"color: rgb(172, 57, 255);\"><\/span><\/p>\n<p style=\"text-wrap: wrap;\"><span style=\"color: rgb(172, 57, 255);\">&gt; summary(learning.test)<\/span><\/p>\n<p style=\"text-wrap: wrap;\">A &nbsp; &nbsp; &nbsp; &nbsp;B &nbsp; &nbsp; &nbsp; &nbsp;C &nbsp; &nbsp; &nbsp; &nbsp;D &nbsp; &nbsp; &nbsp; &nbsp;E &nbsp; &nbsp; &nbsp; &nbsp;F<\/p>\n<p style=\"text-wrap: wrap;\">a:1668 &nbsp; a:2362 &nbsp; a:3717 &nbsp; a:1755 &nbsp; a:1941 &nbsp; a:2509<\/p>\n<p style=\"text-wrap: wrap;\">b:1670 &nbsp; b: 568 &nbsp; b:1024 &nbsp; b:1570 &nbsp; b:1493 &nbsp; b:2491<\/p>\n<p style=\"text-wrap: wrap;\">c:1662 &nbsp; c:2070 &nbsp; c: 259 &nbsp; c:1675 &nbsp; c:1566<\/p>\n<p style=\"text-wrap: wrap;\">\n<\/section>\n<section powered-by=\"xiumi.us\">\n<p style=\"text-indent: 2em;text-wrap: wrap;\">\u63a5\u7740\uff0c\u5c0f\u5e08\u59b9\u5c06\u4f7f\u7528bnlearn\u4e2d\u7684iamb\u51fd\u6570\u8c03\u7528iamb\u65b9\u6cd5\u8fdb\u884c\u8d1d\u53f6\u65af\u7f51\u7edc\u7ed3\u6784\u7684\u5b66\u4e60\uff0c\u8ba9\u5c0f\u5e08\u59b9\u5411\u5927\u5bb6\u7b80\u5355\u5730\u4ecb\u7ecd\u4e00\u4e0b\u8be5iamb\u65b9\u6cd5\uff1a<\/p>\n<p style=\"text-indent: 2em;text-wrap: wrap;\">\n<p style=\"text-indent: 2em;text-wrap: wrap;\">&#8220;iamb&#8221; \u662f &#8220;Inclusion of Ancestral Nodes via Markov Blanket&#8221;\uff08\u901a\u8fc7\u9a6c\u5c14\u79d1\u592b\u6bef\u8986\u76d6\u5305\u542b\u7956\u5148\u8282\u70b9\uff09\u7684\u7f29\u5199\uff0c\u662f\u8d1d\u53f6\u65af\u7f51\u7edc\u6784\u5efa\u4e2d\u7684\u4e00\u79cd\u65b9\u6cd5\u3002\u5b83\u7528\u4e8e\u5728\u7ed9\u5b9a\u6570\u636e\u96c6\u7684\u60c5\u51b5\u4e0b\uff0c\u901a\u8fc7\u8bc6\u522b\u53d8\u91cf\u7684\u9a6c\u5c14\u79d1\u592b\u6bef\u6765\u4f30\u8ba1\u53d8\u91cf\u4e4b\u95f4\u7684\u6982\u7387\u5173\u7cfb\u3002<\/p>\n<p style=\"text-indent: 2em;text-wrap: wrap;\">\n<p style=\"text-align: center;\"><img decoding=\"async\" class=\"rich_pages wxw-img\" data-galleryid=\"\" data-ratio=\"0.3888888888888889\" data-s=\"300,640\" data-src=\"https:\/\/i0.wp.com\/www.biocloudservice.com\/wordpress\/wp-content\/uploads\/2023\/10\/71697786589.jpg?w=640\" data-type=\"jpeg\" data-w=\"1080\" src=\"https:\/\/i0.wp.com\/www.biocloudservice.com\/wordpress\/wp-content\/uploads\/2023\/10\/71697786589.jpg?w=640\" data-recalc-dims=\"1\"><\/p>\n<p style=\"text-indent: 2em;text-wrap: wrap;\">\n<p style=\"text-indent: 2em;text-wrap: wrap;\"><strong>&#8220;iamb&#8221; \u65b9\u6cd5\u7684\u6b65\u9aa4\u5982\u4e0b\uff1a<\/strong><\/p>\n<\/section>\n<ol style=\"padding-left: 40px;list-style-position: outside;\" class=\"list-paddingleft-1\" powered-by=\"xiumi.us\">\n<li><strong>\u521d\u59cb\u9636\u6bb5<\/strong>\uff1a\u5c06\u6bcf\u4e2a\u8282\u70b9\u89c6\u4e3a\u4e00\u4e2a\u72ec\u7acb\u7684\u7f51\u7edc\u3002<\/li>\n<li><strong>\u641c\u7d22\u9636\u6bb5<\/strong>\uff1a\u5bf9\u4e8e\u6bcf\u4e2a\u8282\u70b9\uff0c\u641c\u7d22\u4e0e\u4e4b\u5173\u8054\u7684\u8282\u70b9\uff0c\u5f62\u6210\u4e00\u4e2a\u5019\u9009\u7684\u9a6c\u5c14\u79d1\u592b\u6bef\u3002\u641c\u7d22\u7684\u8fc7\u7a0b\u53ef\u4ee5\u4f7f\u7528\u4e00\u4e9b\u542f\u53d1\u5f0f\u7b97\u6cd5\uff0c\u4f8b\u5982\u904d\u5386\u90bb\u5c45\u8282\u70b9\u3001\u8ba1\u7b97\u6761\u4ef6\u72ec\u7acb\u6027\u6d4b\u8bd5\u7b49\u3002<\/li>\n<li><strong>\u526a\u679d\u9636\u6bb5<\/strong>\uff1a\u901a\u8fc7\u6761\u4ef6\u72ec\u7acb\u6027\u6d4b\u8bd5\u6765\u6392\u9664\u4e00\u4e9b\u4e0d\u7b26\u5408\u6761\u4ef6\u7684\u8282\u70b9\uff0c\u4ece\u800c\u51cf\u5c0f\u9a6c\u5c14\u79d1\u592b\u6bef\u7684\u89c4\u6a21\u3002<\/li>\n<li><strong>\u5408\u5e76\u9636\u6bb5<\/strong>\uff1a\u5c06\u5269\u4f59\u7684\u8282\u70b9\u5408\u5e76\u5230\u5f53\u524d\u8282\u70b9\u7684\u9a6c\u5c14\u79d1\u592b\u6bef\u4e2d\uff0c\u5f62\u6210\u66f4\u5927\u7684\u9a6c\u5c14\u79d1\u592b\u6bef\u3002<\/li>\n<li><strong>\u91cd\u590d\u6b65\u9aa4<\/strong>\uff1a\u91cd\u590d\u4ee5\u4e0a\u6b65\u9aa4\uff0c\u76f4\u5230\u65e0\u6cd5\u518d\u6dfb\u52a0\u65b0\u7684\u8282\u70b9\u4e3a\u6b62\u3002<\/li>\n<\/ol>\n<p style=\"text-wrap: wrap;\" powered-by=\"xiumi.us\">\n<section powered-by=\"xiumi.us\">\n<p style=\"text-indent: 2em;text-wrap: wrap;\">\u901a\u8fc7\u8fd9\u4e2a\u65b9\u6cd5\uff0c\u53ef\u4ee5\u9010\u6b65\u8bc6\u522b\u51fa\u6bcf\u4e2a\u8282\u70b9\u7684\u9a6c\u5c14\u79d1\u592b\u6bef\uff0c\u4ece\u800c\u5efa\u7acb\u8d1d\u53f6\u65af\u7f51\u7edc\u7684\u7ed3\u6784\u3002\u8fd9\u4e2a\u65b9\u6cd5\u7684\u4f18\u70b9\u5728\u4e8e\uff0c\u5b83\u53ef\u4ee5\u5728\u7ed9\u5b9a\u6570\u636e\u96c6\u7684\u60c5\u51b5\u4e0b\uff0c\u901a\u8fc7\u4e00\u4e9b\u7edf\u8ba1\u6d4b\u8bd5\u6765\u63a8\u65ad\u53d8\u91cf\u4e4b\u95f4\u7684\u6761\u4ef6\u72ec\u7acb\u6027\uff0c\u4ece\u800c\u5e2e\u52a9\u786e\u5b9a\u7f51\u7edc\u7ed3\u6784\u3002\u7136\u800c\uff0c\u8fd9\u4e2a\u65b9\u6cd5\u4e5f\u53ef\u80fd\u53d7\u5230\u6570\u636e\u566a\u97f3\u548c\u91c7\u6837\u91cf\u7684\u9650\u5236\u3002\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0c\u901a\u5e38\u9700\u8981\u7ed3\u5408\u9886\u57df\u77e5\u8bc6\u548c\u5176\u4ed6\u7b97\u6cd5\u6765\u5b8c\u5584\u8d1d\u53f6\u65af\u7f51\u7edc\u7684\u6784\u5efa\u3002<\/p>\n<p style=\"text-indent: 2em;text-wrap: wrap;\">\n<p style=\"text-indent: 2em;text-wrap: wrap;\">\u521d\u5b66\u7684\u5c0f\u4f19\u4f34\u4eec\u770b\u5230\u8fd9\u91cc\u53ef\u80fd\u5c31\u5f00\u59cb\u62c5\u5fc3\u4e86\uff0c\u90a3\u4e48\u600e\u4e48\u8fd0\u7528R\u8bed\u8a00\u901a\u8fc7\u5df2\u77e5\u6570\u636e\u8c03\u7528iamb\u65b9\u6cd5\u6784\u5efa\u8d1d\u53f6\u65af\u7f51\u7edc\u5462\uff1f\u5c0f\u5e08\u59b9\u8bf4\uff0c\u53ea\u9700\u4e00\u884c\u4ee3\u7801\uff01<\/p>\n<\/section>\n<section class=\"code-snippet__fix code-snippet__js\">\n<ul class=\"code-snippet__line-index code-snippet__js\">\n<li><\/li>\n<\/ul>\n<pre class=\"code-snippet__js\" data-lang=\"c\"><code><span class=\"code-snippet_outer\">pdag = iamb(learning.test) &nbsp;<\/span><\/code><\/pre>\n<\/section>\n<p style=\"text-indent: 2em;text-wrap: wrap;\" powered-by=\"xiumi.us\">\u521d\u5b66\u7684\u5c0f\u4f19\u4f34\u4eec\uff0c\u53ea\u9700\u8c03\u7528bnlearn\u4e2d\u7684iamb\u51fd\u6570\uff0c\u5e76\u5c06\u7ed9\u5b9a\u7684\u6570\u636e\u96c6\u4f5c\u4e3a\u8f93\u5165\uff0c\u5c31\u5b8c\u6210\u8d1d\u53f6\u65af\u7f51\u7edc\u7684\u7b80\u5355\u6784\u5efa\u5566\uff0c\u662f\u4e0d\u662f\u975e\u5e38\u7b80\u5355\u5462\uff1f\u8ba9\u6211\u4eec\u770b\u770b\u7531\u8be5\u51fd\u6570\u521b\u5efa\u7684\u8d1d\u53f6\u65af\u7f51\u7edc\u662f\u4ec0\u4e48\u6837\uff1a<\/p>\n<section class=\"code-snippet__fix code-snippet__js\">\n<ul class=\"code-snippet__line-index code-snippet__js\">\n<li><\/li>\n<li><\/li>\n<\/ul>\n<pre class=\"code-snippet__js\" data-lang=\"c\"><code><span class=\"code-snippet_outer\">pdag &nbsp;<\/span><\/code><code><span class=\"code-snippet_outer\">pp = graphviz.plot(pdag) &nbsp;<\/span><\/code><\/pre>\n<\/section>\n<p style=\"text-indent: 2em;text-wrap: wrap;\" powered-by=\"xiumi.us\">\n<section powered-by=\"xiumi.us\">\n<p style=\"text-wrap: wrap;\"><span style=\"color: rgb(172, 57, 255);\">&gt; pdag<\/span><\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">Bayesian network learned via Constraint-based methods<\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">model:<\/p>\n<p style=\"text-wrap: wrap;\">[partially directed graph]<\/p>\n<p style=\"text-wrap: wrap;\">nodes: &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 6<\/p>\n<p style=\"text-wrap: wrap;\">arcs: &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;5<\/p>\n<p style=\"text-wrap: wrap;\">undirected arcs: &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 1<\/p>\n<p style=\"text-wrap: wrap;\">directed arcs: &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 4<\/p>\n<p style=\"text-wrap: wrap;\">average markov blanket size: &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 2.33<\/p>\n<p style=\"text-wrap: wrap;\">average neighbourhood size: &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;1.67<\/p>\n<p style=\"text-wrap: wrap;\">average branching factor: &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;0.67<\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">learning algorithm: &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;IAMB<\/p>\n<p style=\"text-wrap: wrap;\">conditional independence test: &nbsp; &nbsp; &nbsp; &nbsp; Mutual Information (disc.)<\/p>\n<p style=\"text-wrap: wrap;\">alpha threshold: &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; 0.05<\/p>\n<p style=\"text-wrap: wrap;\">tests used in the learning procedure: &nbsp;134<\/p>\n<\/section>\n<section style=\"text-align: center;margin-top: 10px;margin-bottom: 10px;line-height: 0;\" powered-by=\"xiumi.us\">\n<section style=\"vertical-align: middle;display: inline-block;line-height: 0;\"><img decoding=\"async\" class=\"rich_pages wxw-img\" data-ratio=\"0.9959839357429718\" data-s=\"300,640\" data-src=\"https:\/\/i0.wp.com\/www.biocloudservice.com\/wordpress\/wp-content\/uploads\/2023\/10\/61697786589.png?w=640\" data-type=\"png\" data-w=\"498\" src=\"https:\/\/i0.wp.com\/www.biocloudservice.com\/wordpress\/wp-content\/uploads\/2023\/10\/61697786589.png?w=640\" data-recalc-dims=\"1\"><\/section>\n<\/section>\n<section powered-by=\"xiumi.us\">\n<p style=\"text-indent: 2em;text-wrap: wrap;\">\u7ec6\u5fc3\u7684\u5c0f\u4f19\u4f34\u4eec\u53ef\u80fd\u53d1\u73b0\u4e86\uff0c\u8282\u70b9A\u548c\u8282\u70b9B\u4e4b\u95f4\u7684\u5f27\u5e76\u975e\u6807\u51c6\u7684\u6709\u5411\u5f27\uff0c\u800c\u662f\u4e00\u79cd\u65e0\u5411\u5f27\uff0c\u8fd9\u53c8\u662f\u4e3a\u4ec0\u4e48\u5462\uff1f\u6211\u4eec\u8c03\u7528score()\u51fd\u6570\u53bb\u8ba1\u7b97\u8282\u70b9A\u3001B\u4e4b\u95f4\u7684BDe\u5f97\u5206\u3002<\/p>\n<p style=\"text-indent: 2em;text-wrap: wrap;\">\n<p style=\"text-indent: 2em;text-wrap: wrap;\">score \u51fd\u6570\u7528\u4e8e\u8ba1\u7b97\u8d1d\u53f6\u65af\u7f51\u7edc\u7684\u5206\u6570\uff0c\u5e2e\u52a9\u8bc4\u4f30\u7f51\u7edc\u7ed3\u6784\u7684\u62df\u5408\u7a0b\u5ea6\uff0c\u4ece\u800c\u53ef\u4ee5\u7528\u6765\u6bd4\u8f83\u4e0d\u540c\u7f51\u7edc\u7ed3\u6784\u4e4b\u95f4\u7684\u597d\u574f\u3002\u8d1d\u53f6\u65af\u7f51\u7edc\u7684\u5206\u6570\u901a\u5e38\u57fa\u4e8e\u6570\u636e\u62df\u5408\u7a0b\u5ea6\u548c\u6a21\u578b\u590d\u6742\u5ea6\u4e24\u4e2a\u56e0\u7d20\u3002\u5177\u4f53\u5730\uff0cscore \u51fd\u6570\u7684\u539f\u7406\u662f\u901a\u8fc7\u4e00\u4e2a\u635f\u5931\u51fd\u6570\u6765\u8861\u91cf\u6570\u636e\u62df\u5408\u7a0b\u5ea6\u548c\u6a21\u578b\u590d\u6742\u5ea6\u4e4b\u95f4\u7684\u6743\u8861\u3002\u5e38\u7528\u7684\u635f\u5931\u51fd\u6570\u4e4b\u4e00\u662f BDe\uff08Bayesian Dirichlet equivalence\uff09\uff0c\u5b83\u8003\u8651\u4e86\u53d8\u91cf\u4e4b\u95f4\u7684\u6761\u4ef6\u6982\u7387\u5206\u5e03\u4ee5\u53ca\u7f51\u7edc\u7684\u7ed3\u6784\u3002<\/p>\n<p style=\"text-indent: 2em;text-wrap: wrap;\">\n<p style=\"text-indent: 2em;text-wrap: wrap;\">\u5176\u4e2d\uff1a<\/p>\n<p style=\"text-indent: 2em;text-wrap: wrap;\">LL \u8868\u793a\u5bf9\u6570\u4f3c\u7136\uff08Log Likelihood\uff09\uff0c\u8861\u91cf\u4e86\u6a21\u578b\u5bf9\u89c2\u6d4b\u6570\u636e\u7684\u62df\u5408\u7a0b\u5ea6\u3002\u4f3c\u7136\u8d8a\u9ad8\uff0c\u6a21\u578b\u8d8a\u80fd\u591f\u89e3\u91ca\u6570\u636e\u3002<\/p>\n<p style=\"text-indent: 2em;text-wrap: wrap;\">|P| \u662f\u6a21\u578b\u4e2d\u7684\u53c2\u6570\u6570\u91cf\uff0c\u4e5f\u5c31\u662f\u7f51\u7edc\u4e2d\u6240\u6709\u7684\u6761\u4ef6\u6982\u7387\u5206\u5e03\u7684\u53c2\u6570\u6570\u91cf\u4e4b\u548c\u3002<\/p>\n<p style=\"text-indent: 2em;text-wrap: wrap;\">N \u662f\u6837\u672c\u6570\u636e\u7684\u5927\u5c0f\u3002<\/p>\n<p style=\"text-indent: 2em;text-wrap: wrap;\">\n<p style=\"text-indent: 2em;text-wrap: wrap;\">LL \u7684\u8ba1\u7b97\u6d89\u53ca\u5230\u89c2\u6d4b\u6570\u636e\u548c\u7f51\u7edc\u7ed3\u6784\uff0c\u901a\u8fc7\u8ba1\u7b97\u8282\u70b9\u6761\u4ef6\u6982\u7387\u5206\u5e03\u548c\u89c2\u6d4b\u6570\u636e\u7684\u5dee\u5f02\u6765\u5224\u65ad\u6570\u636e\u62df\u5408\u7a0b\u5ea6\u3002|P| \u8d8a\u5927\uff0c\u6a21\u578b\u7684\u590d\u6742\u5ea6\u8d8a\u9ad8\uff0c\u800c log(N) \u5219\u662f\u7528\u6765\u60e9\u7f5a\u6a21\u578b\u590d\u6742\u5ea6\u7684\u9879\uff0c\u4ee5\u9632\u6b62\u8fc7\u5ea6\u62df\u5408\u3002\u901a\u8fc7\u8ba1\u7b97 BDe \u5206\u6570\uff0cscore \u51fd\u6570\u53ef\u4ee5\u5e2e\u52a9\u4f60\u6bd4\u8f83\u4e0d\u540c\u7f51\u7edc\u7ed3\u6784\u4e4b\u95f4\u7684\u597d\u574f\uff0c\u9009\u62e9\u6700\u9002\u5408\u6570\u636e\u7684\u7f51\u7edc\u7ed3\u6784\u3002<\/p>\n<p style=\"text-indent: 2em;text-wrap: wrap;\">\n<\/section>\n<section class=\"code-snippet__fix code-snippet__js\">\n<ul class=\"code-snippet__line-index code-snippet__js\">\n<li><\/li>\n<li><\/li>\n<li><\/li>\n<\/ul>\n<pre class=\"code-snippet__js\" data-lang=\"c\"><code><span class=\"code-snippet_outer\">#\u8ba1\u7b97A to B\u548cB to A\u7684BDe\u5206\u6570 &nbsp;<\/span><\/code><code><span class=\"code-snippet_outer\">score(<span class=\"code-snippet__built_in\">set<\/span>.arc(pdag, from = <span class=\"code-snippet__string\">\"A\"<\/span>, to = <span class=\"code-snippet__string\">\"B\"<\/span>), learning.test) &nbsp;<\/span><\/code><code><span class=\"code-snippet_outer\">score(<span class=\"code-snippet__built_in\">set<\/span>.arc(pdag, from = <span class=\"code-snippet__string\">\"B\"<\/span>, to = <span class=\"code-snippet__string\">\"A\"<\/span>), learning.test) &nbsp;<\/span><\/code><\/pre>\n<\/section>\n<p style=\"text-indent: 2em;text-wrap: wrap;\" powered-by=\"xiumi.us\">\n<section powered-by=\"xiumi.us\">\n<p style=\"text-wrap: wrap;\"><span style=\"color: rgb(172, 57, 255);\">&gt; score(set.arc(pdag, from = &#8220;A&#8221;, to = &#8220;B&#8221;), learning.test)<\/span><\/p>\n<p style=\"text-wrap: wrap;\">[1] -24006.73<\/p>\n<p style=\"text-wrap: wrap;\"><span style=\"color: rgb(172, 57, 255);\">&gt; score(set.arc(pdag, from = &#8220;B&#8221;, to = &#8220;A&#8221;), learning.test)<\/span><\/p>\n<p style=\"text-wrap: wrap;\">[1] -24006.73<\/p>\n<p style=\"text-wrap: wrap;\">\n<\/section>\n<section powered-by=\"xiumi.us\">\n<p style=\"text-indent: 2em;text-wrap: wrap;\">\u4ece\u4e0a\u9762\u7684\u8f93\u51fa\u4e2d\u6211\u4eec\u53ef\u4ee5\u770b\u5230\uff0c\u4e24\u4e2a\u53ef\u80fd\u7684\u65b9\u5411\u7684BDe\u5f97\u5206\u662f\u76f8\u7b49\u7684\u7684\uff0c\u6240\u4ee5\u65e0\u6cd5\u786e\u5b9aA\u3001B\u4e24\u4e2a\u8282\u70b9\u4e4b\u95f4\u7684\u65b9\u5411\u3002\u7531\u4e8e\u8d1d\u53f6\u65af\u7f51\u7edc\u7684\u5b9a\u4e49\u65b9\u5f0f\uff0c\u7f51\u7edc\u7ed3\u6784\u5fc5\u987b\u662f\u6709\u5411\u65e0\u73af\u56fe\uff08DAG\uff09;\u5426\u5219 \u5b83\u4eec\u7684\u53c2\u6570\u65e0\u6cd5\u4f30\u8ba1\uff0c\u56e0\u4e3a\u6570\u636e\u7684\u5168\u5c40\u6982\u7387\u5206\u5e03\u5206\u89e3\u4e3a \u5c40\u90e8\u53d8\u91cf\uff08\u6a21\u578b\u4e2d\u6bcf\u4e2a\u53d8\u91cf\u4e00\u4e2a\uff09\u5e76\u4e0d\u5b8c\u5168\u5df2\u77e5\u3002<\/p>\n<p style=\"text-indent: 2em;text-wrap: wrap;\">\n<p style=\"text-indent: 2em;text-wrap: wrap;\">\u5047\u8bbe\u6211\u4eec\u73b0\u5728\u77e5\u9053\u4e86A\u3001B\u7684\u62d3\u6251\u5e8f\uff0c\u5373B\u662fA\u7684\u7236\u8282\u70b9\uff0c\u90a3\u4e48\u6211\u4eec\u53ef\u4ee5\u624b\u52a8\u8bbe\u7f6e\u8be5\u6709\u5411\u5f27\uff1a<\/p>\n<\/section>\n<section class=\"code-snippet__fix code-snippet__js\">\n<ul class=\"code-snippet__line-index code-snippet__js\">\n<li><\/li>\n<li><\/li>\n<\/ul>\n<pre class=\"code-snippet__js\" data-lang=\"c\"><code><span class=\"code-snippet_outer\">#\u624b\u52a8\u4fee\u6539B\u5230A\u7684\u6709\u5411\u5f27 &nbsp;<\/span><\/code><code><span class=\"code-snippet_outer\">dag = <span class=\"code-snippet__built_in\">set<\/span>.arc(pdag, from = <span class=\"code-snippet__string\">\"B\"<\/span>, to = <span class=\"code-snippet__string\">\"A\"<\/span>) &nbsp;<\/span><\/code><\/pre>\n<\/section>\n<section style=\"text-align: center;margin-top: 10px;margin-bottom: 10px;line-height: 0;\" powered-by=\"xiumi.us\">\n<section style=\"vertical-align: middle;display: inline-block;line-height: 0;\"><img decoding=\"async\" class=\"rich_pages wxw-img\" data-ratio=\"0.9959839357429718\" data-s=\"300,640\" data-src=\"https:\/\/i0.wp.com\/www.biocloudservice.com\/wordpress\/wp-content\/uploads\/2023\/10\/31697786590.png?w=640\" data-type=\"png\" data-w=\"498\" src=\"https:\/\/i0.wp.com\/www.biocloudservice.com\/wordpress\/wp-content\/uploads\/2023\/10\/31697786590.png?w=640\" data-recalc-dims=\"1\"><\/section>\n<\/section>\n<p style=\"text-indent: 2em;text-wrap: wrap;\" powered-by=\"xiumi.us\">\u8fd9\u6837\uff0c\u4e00\u4e2a\u5b8c\u6574\u7684\u8d1d\u53f6\u65af\u7f51\u7edc\u7ed3\u6784\u5c31\u521b\u5efa\u5b8c\u6210\u4e86\uff01\u662f\u4e0d\u662f\u975e\u5e38\u8f7b\u677e\u5462\uff0c\u4e0b\u9762\u5c0f\u5e08\u59b9\u5c06\u5e26\u5927\u5bb6\u5728\u5efa\u7acb\u8d1d\u53f6\u65af\u7f51\u7edc\u7ed3\u6784\u7684\u57fa\u7840\u4e0a\u8fdb\u884c\u53c2\u6570\u7684\u62df\u5408\u548c\u6761\u4ef6\u6982\u7387\u7684\u63a8\u65ad\uff0c\u8d1d\u53f6\u65af\u7f51\u7edc\u7684\u53c2\u6570\u62df\u5408\uff08\u6216\u8005\u53eb\u5b66\u4e60\uff09\u662f\u6307\u5728\u5df2\u77e5\u8282\u70b9\u6982\u7387\u5206\u5e03\u65cf\u7684\u60c5\u51b5\u4e0b\uff0c\u901a\u8fc7\u5b66\u4e60\u5176\u6982\u7387\u5206\u5e03\u65cf\u7684\u5177\u4f53\u53c2\u6570\u7ed9\u51fa\u5177\u4f53\u7684\u6982\u7387\u5206\u5e03\uff0c\u5728\u79bb\u6563\u95ee\u9898\u4e2d\uff0c\u5373\u6307\u8ba1\u7b97\u51fa\u4e0d\u540c\u8282\u70b9\u7684\u6761\u4ef6\u6982\u7387\u8868\u683c(Conditional probability table \/CPT)\uff0c\u5c0f\u5e08\u59b9\u5c06\u4f7f\u7528\u6700\u5927\u4f3c\u7136\u4f30\u8ba1\uff08mle\uff09\u7684\u65b9\u6cd5\u5411\u5927\u5bb6\u6f14\u793a\uff1a<\/p>\n<section class=\"code-snippet__fix code-snippet__js\">\n<ul class=\"code-snippet__line-index code-snippet__js\">\n<li><\/li>\n<li><\/li>\n<li><\/li>\n<\/ul>\n<pre class=\"code-snippet__js\" data-lang=\"c\"><code><span class=\"code-snippet_outer\">#\u4f7f\u7528mle\u8fdb\u884c\u53c2\u6570\u62df\u5408 &nbsp;<\/span><\/code><code><span class=\"code-snippet_outer\">fitted = bn.fit(dag, learning.test, method = <span class=\"code-snippet__string\">\"mle\"<\/span>) &nbsp;<\/span><\/code><code><span class=\"code-snippet_outer\">fitted &nbsp;<\/span><\/code><\/pre>\n<\/section>\n<p style=\"text-indent: 2em;text-wrap: wrap;\" powered-by=\"xiumi.us\">\n<section powered-by=\"xiumi.us\">\n<p style=\"text-wrap: wrap;\"><span style=\"color: rgb(172, 57, 255);\">&gt; fitted<\/span><\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">Bayesian network parameters<\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">Parameters of node A (multinomial distribution)<\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">Conditional probability table:<\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">B<\/p>\n<p style=\"text-wrap: wrap;\">A &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;a &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;b &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;c<\/p>\n<p style=\"text-wrap: wrap;\">a 0.60457240 0.07394366 0.09565217<\/p>\n<p style=\"text-wrap: wrap;\">b 0.31456393 0.64964789 0.26956522<\/p>\n<p style=\"text-wrap: wrap;\">c 0.08086367 0.27640845 0.63478261<\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">Parameters of node B (multinomial distribution)<\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">Conditional probability table:<\/p>\n<p style=\"text-wrap: wrap;\">a &nbsp; &nbsp; &nbsp;b &nbsp; &nbsp; &nbsp;c<\/p>\n<p style=\"text-wrap: wrap;\">0.4724 0.1136 0.4140<\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">Parameters of node C (multinomial distribution)<\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">Conditional probability table:<\/p>\n<p style=\"text-wrap: wrap;\">a &nbsp; &nbsp; &nbsp;b &nbsp; &nbsp; &nbsp;c<\/p>\n<p style=\"text-wrap: wrap;\">0.7434 0.2048 0.0518<\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">Parameters of node D (multinomial distribution)<\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">Conditional probability table:<\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">, , C = a<\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">A<\/p>\n<p style=\"text-wrap: wrap;\">D &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;a &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;b &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;c<\/p>\n<p style=\"text-wrap: wrap;\">a 0.80081301 0.09251810 0.10530547<\/p>\n<p style=\"text-wrap: wrap;\">b 0.09024390 0.80209171 0.11173633<\/p>\n<p style=\"text-wrap: wrap;\">c 0.10894309 0.10539019 0.78295820<\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">, , C = b<\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">A<\/p>\n<p style=\"text-wrap: wrap;\">D &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;a &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;b &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;c<\/p>\n<p style=\"text-wrap: wrap;\">a 0.18079096 0.88304094 0.24695122<\/p>\n<p style=\"text-wrap: wrap;\">b 0.13276836 0.07017544 0.49390244<\/p>\n<p style=\"text-wrap: wrap;\">c 0.68644068 0.04678363 0.25914634<\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">, , C = c<\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">A<\/p>\n<p style=\"text-wrap: wrap;\">D &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;a &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;b &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;c<\/p>\n<p style=\"text-wrap: wrap;\">a 0.42857143 0.34117647 0.13333333<\/p>\n<p style=\"text-wrap: wrap;\">b 0.20238095 0.38823529 0.44444444<\/p>\n<p style=\"text-wrap: wrap;\">c 0.36904762 0.27058824 0.42222222<\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">Parameters of node E (multinomial distribution)<\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">Conditional probability table:<\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">, , F = a<\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">B<\/p>\n<p style=\"text-wrap: wrap;\">E &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;a &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;b &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;c<\/p>\n<p style=\"text-wrap: wrap;\">a 0.80524979 0.20588235 0.11937378<\/p>\n<p style=\"text-wrap: wrap;\">b 0.09737511 0.17973856 0.11448141<\/p>\n<p style=\"text-wrap: wrap;\">c 0.09737511 0.61437908 0.76614481<\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">, , F = b<\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">B<\/p>\n<p style=\"text-wrap: wrap;\">E &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;a &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;b &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;c<\/p>\n<p style=\"text-wrap: wrap;\">a 0.40050804 0.31679389 0.23759542<\/p>\n<p style=\"text-wrap: wrap;\">b 0.49026249 0.36641221 0.50667939<\/p>\n<p style=\"text-wrap: wrap;\">c 0.10922947 0.31679389 0.25572519<\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">Parameters of node F (multinomial distribution)<\/p>\n<p style=\"text-wrap: wrap;\">\n<p style=\"text-wrap: wrap;\">Conditional probability table:<\/p>\n<p style=\"text-wrap: wrap;\">a &nbsp; &nbsp; &nbsp;b<\/p>\n<p style=\"text-wrap: wrap;\">0.5018 0.4982<\/p>\n<\/section>\n<section powered-by=\"xiumi.us\">\n<p style=\"text-indent: 2em;text-wrap: wrap;\">\n<p style=\"text-indent: 2em;text-wrap: wrap;\">\u901a\u8fc7$\u7b26\u53f7\uff0c\u53ef\u4ee5\u8bbf\u95ee\u6307\u5b9a\u8282\u70b9\u7684\u6761\u4ef6\u6982\u7387\u5206\u5e03\u8868\uff0c\u4f8b\u5982\u901a\u8fc7fitted$D\u8bbf\u95ee\u8282\u70b9D\u7684CPT\uff0c\u4e5f\u53ef\u4ee5\u901a\u8fc7\u7ed8\u56fe\u7684\u65b9\u5f0f\uff0c\u66f4\u4e3a\u76f4\u89c2\u5730\u89c2\u5bdf\u6211\u4eec\u9700\u8981\u7684CPT\uff1a<\/p>\n<\/section>\n<section class=\"code-snippet__fix code-snippet__js\">\n<ul class=\"code-snippet__line-index code-snippet__js\">\n<li><\/li>\n<li><\/li>\n<li><\/li>\n<\/ul>\n<pre class=\"code-snippet__js\" data-lang=\"c\"><code><span class=\"code-snippet_outer\">#\u901a\u8fc7\u7ed8\u56fe\u89c2\u5bdfCPT &nbsp;<\/span><\/code><code><span class=\"code-snippet_outer\">bn.fit.barchart(fitted$D) &nbsp;<\/span><\/code><code><span class=\"code-snippet_outer\">bn.fit.dotplot(fitted$D) &nbsp;<\/span><\/code><\/pre>\n<\/section>\n<p style=\"text-indent: 2em;text-wrap: wrap;\" powered-by=\"xiumi.us\">\n<section style=\"text-align: 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