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        <datestamp>2026-10-14T16:08:00Z</datestamp>
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          <dc:title>Data for Retail Demand Forecasting under Promotions</dc:title>
          <dc:creator>doohee chung (24477425)</dc:creator>
          <dc:subject>Machine learning not elsewhere classified</dc:subject>
          <dc:subject>machine learning</dc:subject>
          <dc:subject>data science</dc:subject>
          <dc:description>&lt;p dir="ltr"&gt;Forecasts of every method for every evaluation window, the calendar weeks and promotion flags of each window, the values behind every table and figure, and the code that recomputes all reported numbers for the article. The Dominick’s store-week sales are not redistributed because the Kilts Center provides them for academic research only; code/rebuild_truth.py rebuilds them exactly from the raw files available at &lt;a href="https://www.chicagobooth.edu/research/kilts/research-data/dominicks" target="_blank"&gt;https://www.chicagobooth.edu/research/kilts/research-data/dominicks&lt;/a&gt;. See README.md&lt;/p&gt;&lt;p dir="ltr"&gt;&lt;br&gt;&lt;/p&gt;</dc:description>
          <dc:date>2026-10-14T16:08:00Z</dc:date>
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