{"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":274,"pdf_page":290,"physical_index":290,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"9b22f50437adb75c39b63d3fedff3981aeae9d428367af1b605e42a8b14848db"},"chapter":"第9章","content":"9.2 L2 正则化\n\n正则化在机器学习领域很重要，主要是针对模型过拟合问题而提出来的。在前面的章节中，我们一直在探讨如何让训练误差降至最低。对于正则化，简单来说，就是不要过于信赖训练样本。如图9-9所示，从过拟合曲线可以看出：随着进行越来越多次迭代，训练误差会减少，越来越少，并一直减少。\n\n训练数据（TrainingData）曲线会不断下降，最终它会在某种程度上收敛于底端。但实际上验证数据（ValidationData）曲线开始上升。验证数据是我们真正要关注的。尽管我们在对训练样本进行训练，但想要泛化到新的样本，也就是测试样本。我们希望将样本的损失控制在较低的范围。那么如何抑制验证数据曲线上升呢？这表示什么情况呢？首先说明出现了过拟合。我们在处理训练数据样本方面做得很好，开始在某种程度上过拟合训练数据样本的一些独\n\n人工智能与大数据技术导论\n\n274","previous_page":273,"next_page":275}