{"url":"https://iblog.ridge-i.com/entry/2026/04/01/155659","provider_url":"https://hatena.blog","height":"190","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fiblog.ridge-i.com%2Fentry%2F2026%2F04%2F01%2F155659\" title=\"Out-of-Fold Predictions for Stacking ML Models - Ridge-institute R&amp;D Blog\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","image_url":"https://cdn-ak.f.st-hatena.com/images/fotolife/K/Knorlax/20260324/20260324225314.png","description":"Hello everyone, I\u2019m Kien, an AI engineer at Ridge-i. Today, I\u2019d like to walk you through a common issue that can arise in machine learning systems, and share an effective way to address it. Introduction AI medical case study and problem definition How to solve the problem Things to note How many fol\u2026","categories":[],"published":"2026-04-01 15:56:59","width":"100%","author_url":"https://blog.hatena.ne.jp/Knorlax/","blog_url":"https://iblog.ridge-i.com/","blog_title":"Ridge-institute R&D Blog","provider_name":"Hatena Blog","author_name":"Knorlax","version":"1.0","type":"rich","title":"Out-of-Fold Predictions for Stacking ML Models"}