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[{"title": "A Step-by-Step Guide to Feature Engineering for Multivariate Time ...", "href": "https://towardsdatascience.com/a-step-by-step-guide-to-feature-engineering-for-multivariate-time-series-162ccf232e2f", "body": "Automated Feature Engineering. Feature engineering involves extracting and curating explanatory variables. It is a key stage in any data science project. The quality of the features is a central aspect of the performance of models. Because of this, data scientists spend a lot of time in this process. Yet, feature engineering is often an ad-hoc ..."}, {"title": "FP&A Tips: How to Improve Forecasting Accuracy in 2023? - Abacum", "href": "https://www.abacum.io/blog/6-ways-to-improve-forecast-accuracy", "body": "According to FP&A trends, \"The forecast is accurate if the actuals tend to match the forecast within \"small\" variances.\" Another definition they highlighted states, \"The forecast is accurate when all the assumptions and decisions are sound, correctly captured, sized and timed to.\""}, {"title": "A Comparative Study of Demand Forecasting Models for a Multi-Channel ...", "href": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9514716/", "body": "A hybrid genetic algorithm-based XGBoost forecasting methodology is developed. This study empirically demonstrates the significance of feature engineering in forecasting the prices of stocks: Wang et al. To overcome the challenges of predicting rental bike demand on an hourly basis, a data mining technique is used."}]