{"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":269,"pdf_page":285,"physical_index":285,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"f03960796ab7049a23de59a2c128931d1d795a95adfc197cbcd876c9a857b1cd"},"chapter":"第9章","content":"这些特征值现在是分桶索引。请注意，这些索引被视为离散特征。通常情况下，这些特征将被进一步转换为独热编码表示，但这是以透明方式实现的。要为分桶特征定义特征列，我们可以使用 bucketized column（而不是使用numeric column），bucketized column 将数字列作为输入，并使用boundaries参数中指定的分桶边界将其转换为分桶特征。以下代码为households和longitude定义了分桶特征列。get\\_quantile\\_based\\_boundaries函数会根据分位数（quantile）计算边界（boundaries），以便每个分桶包含相同数量的元素。\n\n在前面的代码块中，两个实值列（即households和longitude）已被转换为分桶特征列。剩下的任务是对其余的列进行分桶，然后运行代码来训练模型。我们使用了分位数技巧，通过这种方式选择分桶边界后，每个分桶将包含相同数量的样本。\n\n第9章 TensorFlow 高级知识\n\n269","previous_page":268,"next_page":270}