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A general framework for evaluating real-time bioaerosol classification algorithms
November 2025 • Marie-Pierre Meurville, Bernard Clot, Sophie Erb, Mária Lbadaoui-Darvas, Fiona Tummon, Gian-Duri Lieberherr, Benoît Crouzy, Marie-Pierre Meurville, B…
Abstract. Advances in automatic bioaerosol monitoring require updated approaches to evaluate particle classification algorithms. We present a training and evaluation framework based on three metrics: (1) Kendall’s Tau correlation between predicted and manual concentrations, (2) scaling factor, to assess identification efficiency, and (3) off-season noise ratio, quantifying off-season false predictions. Metrics are computed per class across confidence thresholds and five stations stations, and visualised in graphs …
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Computer Science
Artificial Intelligence
Data Mining
Machine Learning
Boosting (Machine Learning)
Visualization (Graphics)
Performance Indicator
Random Forest
Training, Validation, And Test Data Sets
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Ensemble Learning
Support Vector Machine
Algorithm
Data And Information Visualization
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