An expert-informed and interpretable Naive Bayes framework for forest seedling classification from small samples

Key Points

• Accurate classification of forest seedlings was achieved using the naive bayes model, improving predictive performance.
• The model handles small sample sizes effectively, facilitating reliable identification of different seedling types.
• Assessment utilized an expert-informed approach to enhance the interpretability of classification results in forestry.
• This work supports better seedling management, suggesting a novel method applicable in forest ecology.