{"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":161,"pdf_page":177,"physical_index":177,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"b90ebce45fd1ef128574c7038141446be72bb3af254a2d6440a8e00695f07b3d"},"chapter":"第5章","content":"5.7.2 scikit-learn\n\n编写机器学习模型不容易，但使用机器学习模型非常简单，读者只需套用现有的框架即可。现有的框架可以是某种编程环境中的程序包，或者一款成熟的机器学习商业软件。scikit-learn是一个针对机器学习的强大Python库，主要用于构建模型，使用诸如Numpy、SciPy和Matplotlib等库构建，如图5-9所示，对于统计建模技术（如分类、回归、集群等）非常有效。scikit-learn的特性包括监督式学习算法、非监督式学习算法和交叉验证，官网地址是http://scikit-learn.org/。scikit-learn的优点是可以使用许多shell算法，提供高效的数据挖掘；缺点是不是最好的模型构建库，GPU使用不高效。\n\nPython中有完备的机器学习库sklearn，它整合了现有的众多传统的机器学习模型，这些模型的算法已经在程序包中编写好，用户无须知道算法的原理，也无须懂得模型的含义，甚至无须会编程，即可调用程序包，执行并得到我们需要的结果。整个过程不过只是几行代码，就像把大象放到冰箱一样，只需三步。下面我们以Python为例，来看看它如何解决机器学习经典案例titanic沉船生存预测，如表5-7所示。\n\n第5章 模型\n\n161","previous_page":160,"next_page":162}