Lanhui Wang | Balancing scale and interpretability in analytical applications with sklearn and e
285 views · Published 6 October 2016 · 40:29 · Indexed 14 November 2026
Channel: PyData · 2016 · Science & Technology
PyData Carolinas 2016 We present a machine learning framework using ensemble learning to combine models developed by multiple analysts for distinct subsets of a large feature space. We apply the framework to retail sales data, but its design can accommodate other types of target variables. This is a novel application of ensemble learning since it addresses both analytical and organizational challenges. 00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details. Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps
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