Climate Prediction

Problem

Missing inputs and temporal patterns require deliberate preparation before regression models can be compared.

Objective

Develop preprocessing workflows and compare regression approaches for a climate-prediction task.

Approach

Impute missing values, scale features, derive date-based features, and compare models with cross-validation.

Implementation

Built preprocessing workflows and compared regression models. Used Optuna for hyperparameter optimization alongside cross-validation.

Challenges to investigate

Preprocessing and parameter search must be evaluated consistently. The supplied CV does not include the dataset, split strategy, or experiment logs.

The source does not document the project’s actual obstacles; the following is a technical consideration, not a retrospective claim.

Documented outcomes

The CV documents the preprocessing, model comparison, and tuning workflow. It does not supply verified comparative scores.

Technical reflection

Model comparison is more informative when preprocessing and validation choices are explicit and consistent.

This reflection follows from the documented method; it is not presented as a measured project outcome.