{"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":271,"pdf_page":287,"physical_index":287,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"83519339b5b9b2ac511b47bf01ea16f1332f813dd20d6d9ef669e2703ba918d0"},"chapter":"第9章","content":"9.1.4 特征交叉代码实例\n\n交叉组合的两个（或更多个）特征是使用线性模型来学习非线性关系的一种聪明做法。在我们的例子中，如果只使用latitude特征进行学习，那么该模型可能会发现在一个特定纬度(或在一个特定纬度范围内，因为我们已经将其分桶)的城市街区更可能比其他街区住房成本高昂。longitude特征的情况与此类似。但是，如果我们将longitude与latitude交叉组合，那么产生的交叉组合特征则代表一个明确的城市街区。如果模型发现某些城市街区（位于特定纬度和经度范围内）更可能比其他街区住房成本高昂，那么就是比单独使用两个特征更合适。\n\n目前，特征列API仅支持交叉组合离散特征。如果要组合两个连续的值（比如latitude或longitude），我们可以对其进行分桶。如果交叉组合latitude和longitude特征（例如，longitude被分到2个分桶中，而latitude有3个分桶），那么我们实际上会得到6个交叉组合的二值特征（binaryfeature）。当我们训练模型时，每个特征都会分别获得自己的权重。\n\n第9章 TensorFlow高级知识\n\n271","previous_page":270,"next_page":272}