{"description":"Satyaki Roy, Shimpei Ikeno, and Yuta Suzuki Global ML-powered methods such as Gradient Boosted Trees for time series Why do we need global models? In the last blog post, we saw how to train and forecast individual time series data and aggregate the results. Training forecasting models for each serie\u2026","image_url":"https://cdn-ak.f.st-hatena.com/images/fotolife/n/nri-atlaxblogs/20250602/20250602101645.jpg","title":"Practical Theory for Time Series Forecasting Models 4 \uff0dA Case of the Past Kaggle Competition\uff0d","author_url":"https://blog.hatena.ne.jp/nri-atlaxblogs/","blog_title":"atlax blogs","height":"190","width":"100%","version":"1.0","provider_name":"Hatena Blog","published":"2023-03-01 00:00:00","categories":["\u30c7\u30fc\u30bf\u30a2\u30ca\u30ea\u30c6\u30a3\u30af\u30b9","\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9"],"type":"rich","url":"https://atlaxblogs.nri.co.jp/entry/20230301","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fatlaxblogs.nri.co.jp%2Fentry%2F20230301\" title=\"Practical Theory for Time Series Forecasting Models 4 \uff0dA Case of the Past Kaggle Competition\uff0d - atlax blogs\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","provider_url":"https://hatena.blog","author_name":"nri-atlaxblogs","blog_url":"https://atlaxblogs.nri.co.jp/"}