Machine learning method to identify residential PV adopters, reduce soft costs

An international research team used XGBoost algorithm to predict PV adoption among homeowners. The algorithm showed improved performance over logistic regression in reducing customer acquisition costs and identifying new market opportunities for PV companies. The new methodology can help reduce soft costs for residential solar photovoltaics.

Source:

https://www.pv-magazine.com/2023/05/05/machine-learning-method-to-identify-residential-pv-adopters-reduce-soft-costs/

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