{"resolved":true,"match_type":"uuid","source_type":"original_book","book_id":"cf76bc49-7e9b-4f42-bee8-3050a9fb9feb","title":"智慧的疆界 从图灵机到人工智能","author":null,"edition":null,"publisher":null,"year":null,"isbn":"9787111778004","requested_by":"printed_page","book":{"source_type":"original_book","book_id":"cf76bc49-7e9b-4f42-bee8-3050a9fb9feb","id":"cf76bc49-7e9b-4f42-bee8-3050a9fb9feb","uuid":"cf76bc49-7e9b-4f42-bee8-3050a9fb9feb","title":"智慧的疆界 从图灵机到人工智能","normalized_title":"智慧的疆界从图灵机到人工智能","author":null,"edition":null,"publisher":null,"year":null,"isbn":"9787111778004","isbns":["9787111778004","9787111695714"],"parsed":true,"ai_readable":true,"document_type":"book","page_count":456,"navigation_url":"https://workshop.closeclaw.top/ai/book/cf76bc49-7e9b-4f42-bee8-3050a9fb9feb","title_url":"https://workshop.closeclaw.top/ai/title/%E6%99%BA%E6%85%A7%E7%9A%84%E7%96%86%E7%95%8C%20%E4%BB%8E%E5%9B%BE%E7%81%B5%E6%9C%BA%E5%88%B0%E4%BA%BA%E5%B7%A5%E6%99%BA%E8%83%BD","fixed_page_url_template":"https://workshop.closeclaw.top/ai/book/cf76bc49-7e9b-4f42-bee8-3050a9fb9feb/page/{printed_page}","path_api_url_template":"https://workshop.closeclaw.top/api/ai/book/cf76bc49-7e9b-4f42-bee8-3050a9fb9feb/page/{printed_page}","read_url":"https://workshop.closeclaw.top/api/ai/read/cf76bc49-7e9b-4f42-bee8-3050a9fb9feb","page_url":"https://workshop.closeclaw.top/api/ai/books/cf76bc49-7e9b-4f42-bee8-3050a9fb9feb/page","search_url":"https://workshop.closeclaw.top/api/ai/books/cf76bc49-7e9b-4f42-bee8-3050a9fb9feb/search"},"page":{"printed_page":202,"pdf_page":217,"physical_index":217,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"bb1d05bb83e933263010fe264e61e1f086ecda6f237b1d3f961f654958321b46"},"chapter":"内容简介","content":"果看起来似乎就豁然开朗了。\n\n上面这个二维坐标系其实表达了不止两个维度的信息：以收件人数量为横坐标，以邮件长度为纵坐标，还有以不同点（空心点和实心点）表示的结果。引入第二个判别特征之后，原本分布在一维坐标轴上的邮件柱状统计图变成了分布在二维平面上的点，这时，可以发现在一维坐标轴上犬牙交错、难以直接划分开的垃圾邮件和非垃圾邮件在二维平面中居然是泾渭分明的，区分得非常完美（当然，这里是笔者为了讲解效果特意处理过的数据，实际情况中两个特征肯定仍是不足以完美区分出垃圾邮件和非垃圾邮件的）。\n\n假如两个特征真的足以将是否垃圾邮件如此完美地区分开，那我们只需要在该二维平面里，沿着两类邮件的中间画出一条分界线，将平面分成两部分。当有一封新的邮件输入时，就将其按照收件人数量和邮件长度映射到该平面中，如图 6-16 中五角星所示。如果它分布在属于垃圾邮件一边的空间，那它就被判别为垃圾邮件，否则它就是一封非垃圾邮件。\n\n这个分类器的思路很符合正常人的逻辑思维习惯，事实上也确实是行之有效的，机器学习中把这种分类方法称为“线性分类器”，它是一种基础但在机器学习中极为常见的应用方式。不过，思路虽然想明白了，但在具体操作层面上我们仍有一个问题没有解决：这里并没有定义清楚到底如何在二维平面里沿着两类邮件的中间画出一条直线。\n\n202\n\n第三部分 第三波高潮","previous_page":201,"next_page":203}