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的云端执行记录与这份本地标准输出分开解释。","sha256":"74b1002921cba22fc89835fb6b097d947e130308314ca16a5926cd5568a6c6a0","chapter":{"id":"course","title":"已完成的基准运行"},"unit":{"id":"notebook-blocks/2808d2d9691f4492a32d74b6ab87a431","title":"已完成的基准运行"},"page":{"id":"reading-opening","title":"已完成的基准运行","number":1},"sectionTitle":"已完成的基准运行","currentQuestion":"已完成的基准运行","sourceSlides":[],"knowledgeBlock":null,"formulas":[],"previousBlock":"b-2393a211efb6f39ed0f1f359","nextBlock":"b-c8d4ffabc424c8c186ee58be","prerequisites":[{"id":"b-2393a211efb6f39ed0f1f359","url":"#b-2393a211efb6f39ed0f1f359","role":"section-title"},{"id":"b-85982c45193aa7db7e072802","url":"#b-85982c45193aa7db7e072802","role":"problem-context"}],"relatedBlocks":[]},{"id":"b-c8d4ffabc424c8c186ee58be","type":"pre","scope":"document","url":"https://codingai-lec03.pages.dev/course/notebook-blocks/2808d2d9691f4492a32d74b6ab87a431.html#b-c8d4ffabc424c8c186ee58be","content":"```\nrandom sample split {'ntrain': 180, 'ntest': 60, 'overlapping_groups': 12, 'batch_mean_RMSE': 0.7821631194429031, 'x_only_RMSE': 2.3574347161692795}\nnew batch split {'ntrain': 180, 'ntest': 60, 'overlapping_groups': 0, 'batch_mean_RMSE': 2.115187164028426, 'x_only_RMSE': 1.798035324219997}\nclaim tested: does low random-split error predict performance in unseen acquisition groups?\n\n```","sha256":"42124848ccd8b92f5f1cfff56738e13d724914540fef9149ada772fa6f73a411","chapter":{"id":"course","title":"已完成的基准运行"},"unit":{"id":"notebook-blocks/2808d2d9691f4492a32d74b6ab87a431","title":"已完成的基准运行"},"page":{"id":"reading-opening","title":"已完成的基准运行","number":1},"sectionTitle":"已完成的基准运行","currentQuestion":"已完成的基准运行","sourceSlides":[],"knowledgeBlock":null,"formulas":[],"previousBlock":"b-c6f7eb2e6ba95d23dec72913","nextBlock":"b-cbf77ec391607f100b202808","prerequisites":[{"id":"b-2393a211efb6f39ed0f1f359","url":"#b-2393a211efb6f39ed0f1f359","role":"section-title"},{"id":"b-85982c45193aa7db7e072802","url":"#b-85982c45193aa7db7e072802","role":"problem-context"}],"relatedBlocks":[]},{"id":"b-cbf77ec391607f100b202808","type":"p","scope":"document","url":"https://codingai-lec03.pages.dev/course/notebook-blocks/2808d2d9691f4492a32d74b6ab87a431.html#b-cbf77ec391607f100b202808","content":"先比较组重叠，再解释RMSE。随机划分中“批次均值”可能很好，是因为测试批次在训练中已出现；新批次的默认均值通常失效。x基线也未必足够好，因为目标仍含未知偏置。不能因此宣布x无用，也不能仅换复杂网络就假定问题解决。","sha256":"d946bf0599c4437cdc6d82e8d33de4d1c61adb0bd5c88ac00fbce95e4fe280e3","chapter":{"id":"course","title":"已完成的基准运行"},"unit":{"id":"notebook-blocks/2808d2d9691f4492a32d74b6ab87a431","title":"已完成的基准运行"},"page":{"id":"reading-opening","title":"已完成的基准运行","number":1},"sectionTitle":"已完成的基准运行","currentQuestion":"已完成的基准运行","sourceSlides":[],"knowledgeBlock":null,"formulas":[],"previousBlock":"b-c8d4ffabc424c8c186ee58be","nextBlock":"b-c0a2e4e3864e239d367e5c4d","prerequisites":[{"id":"b-2393a211efb6f39ed0f1f359","url":"#b-2393a211efb6f39ed0f1f359","role":"section-title"},{"id":"b-85982c45193aa7db7e072802","url":"#b-85982c45193aa7db7e072802","role":"problem-context"}],"relatedBlocks":[]},{"id":"b-c0a2e4e3864e239d367e5c4d","type":"p","scope":"document","url":"https://codingai-lec03.pages.dev/course/notebook-blocks/2808d2d9691f4492a32d74b6ab87a431.html#b-c0a2e4e3864e239d367e5c4d","content":"把自己的研究改写为一个具体契约：预测时真正可取得哪些输入？新样本指新个体、新地点还是新时间？最简单而强的基线是什么？哪个分组必须整体留出？只有先固定这些问题，LAB01的冻结读出、LAB02的微调、LAB10的定位或LAB13的条件生成才有可比较的含义。下一步仅把偏置标准差3改成0，检验划分差距是否缩小；这是能改变本例解释的反证。不要将这组构造数据的单次RMSE推广为现实效应大小。","sha256":"bb0108d603afce1835c02befacbeabdc04bfaf27963a327c171e9075f8e3c85d","chapter":{"id":"course","title":"已完成的基准运行"},"unit":{"id":"notebook-blocks/2808d2d9691f4492a32d74b6ab87a431","title":"已完成的基准运行"},"page":{"id":"reading-opening","title":"已完成的基准运行","number":1},"sectionTitle":"已完成的基准运行","currentQuestion":"已完成的基准运行","sourceSlides":[],"knowledgeBlock":null,"formulas":[],"previousBlock":"b-cbf77ec391607f100b202808","nextBlock":null,"prerequisites":[{"id":"b-2393a211efb6f39ed0f1f359","url":"#b-2393a211efb6f39ed0f1f359","role":"section-title"},{"id":"b-85982c45193aa7db7e072802","url":"#b-85982c45193aa7db7e072802","role":"problem-context"}],"relatedBlocks":[]}]}