paper
2021
Local & station forecasting
New model or method
Classical ML (trees, GP, linear, kernels)3–15 days Journal
2021-10-20
004
Oct 2021
Susmita Sen, Sumit Saha, Sudipta Chaki et al.
Computational Intelligence and Machine Learning
PCA-reduced AdaBoost on station records predicts mid-term temperature with R2 of 0.992, reported as beating other tested models.
Analysis of PCA based AdaBoost Machine Learning Model for Predict Mid-Term Weather Forecasting
In one sentence. PCA-reduced AdaBoost on station records predicts mid-term temperature with R2 of 0.992, reported as beating other tested models.
Labels
- Topic
- Local & station forecasting
- Type
- New model or method
- Method
- Classical ML (trees, GP, linear, kernels)
- Time scale
- 3–15 days
- Domain
- Local / station
- Data
- Station / in-situ
- Status
- Research
- Identifiers
- DOI:10.36647/ciml/02.02.a005 OpenAlex:W4312670749
- Added
- 2026-10-22
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