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Mitsui&Co. Commodity Prediction Challenge (Kaggle)

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Goal

Build a predictive model for the Mitsui&Co. competition using lag-based signals and a reproducible inference workflow.

What I did

  • Implemented a single-lag + grouped-lag approach for organizing targets/features
  • Trained an ExtraTrees-based model as a strong non-linear baseline
  • Structured the notebook for Kaggle submission (stable paths, fixed seed, clean sections)

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