{"resolved":true,"match_type":"uuid","source_type":"original_book","book_id":"cd4f7678-cd9b-4971-bde0-e9ad46a6cc71","title":"人工智能与大数据技术导论","author":null,"edition":null,"publisher":null,"year":null,"isbn":"9787302517986","requested_by":"printed_page","book":{"source_type":"original_book","book_id":"cd4f7678-cd9b-4971-bde0-e9ad46a6cc71","id":"cd4f7678-cd9b-4971-bde0-e9ad46a6cc71","uuid":"cd4f7678-cd9b-4971-bde0-e9ad46a6cc71","title":"人工智能与大数据技术导论","normalized_title":"人工智能与大数据技术导论","author":null,"edition":null,"publisher":null,"year":null,"isbn":"9787302517986","isbns":["9787302517986"],"parsed":true,"ai_readable":true,"document_type":"book","page_count":490,"navigation_url":"https://workshop.closeclaw.top/ai/book/cd4f7678-cd9b-4971-bde0-e9ad46a6cc71","title_url":"https://workshop.closeclaw.top/ai/title/%E4%BA%BA%E5%B7%A5%E6%99%BA%E8%83%BD%E4%B8%8E%E5%A4%A7%E6%95%B0%E6%8D%AE%E6%8A%80%E6%9C%AF%E5%AF%BC%E8%AE%BA","fixed_page_url_template":"https://workshop.closeclaw.top/ai/book/cd4f7678-cd9b-4971-bde0-e9ad46a6cc71/page/{printed_page}","path_api_url_template":"https://workshop.closeclaw.top/api/ai/book/cd4f7678-cd9b-4971-bde0-e9ad46a6cc71/page/{printed_page}","read_url":"https://workshop.closeclaw.top/api/ai/read/cd4f7678-cd9b-4971-bde0-e9ad46a6cc71","page_url":"https://workshop.closeclaw.top/api/ai/books/cd4f7678-cd9b-4971-bde0-e9ad46a6cc71/page","search_url":"https://workshop.closeclaw.top/api/ai/books/cd4f7678-cd9b-4971-bde0-e9ad46a6cc71/search"},"page":{"printed_page":167,"pdf_page":183,"physical_index":183,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"171f0f665cd32fddbd26b3011072e6099d733967409ba45c2790806601682f8d"},"chapter":"第6章","content":"6.1.4 分类与回归树分析\n\n决策树是机器学习预测建模的一类重要算法，可以用二叉树来解释决策树模型。这是根据算法和数据结构建立的二叉树，并不难理解。每个节点代表一个输入变量以及变量的分叉点(假设是数值变量）。如图6-5所示是决策树的例子。\n\n树的叶节点包括用于预测的输出变量y。通过树的各分支到达叶节点，并输出对应叶节点的分类值。树可以进行快速的学习和预测。通常并不需要对数据做特殊的处理，就可以使用这个方法对多种问题得到准确的结果。\n\n6.1.5 朴素贝叶斯\n\n朴素贝叶斯（NaiveBayes）是一个简单但异常强大的预测建模算法。这个模型包括两种概率，它们可以通过训练数据直接计算得到：（1）每个类的概率；（2）给定x值的情况下，每个类的条件概率。根据贝叶斯定理（见图6-6），一旦完成计算，就可以使用概率模型针对新的数据进行预测。当你的数据为实数时，通常假设服从高斯分布（钟形曲线），这样可以很容易地预测这些概率。\n\n第6章 机器学习算法\n\n167","previous_page":166,"next_page":168}