A taxonomy-based feature selection method that selects whole categories of trajectory features gives comparable or better classification results than forward and backward selection, but the gains are not statistically significant.
A review of feature selection methods based on meta-heuristic algorithms,
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Towards Interpretable and Efficient Feature Selection in Trajectory Datasets: A Taxonomic Approach
A taxonomy-based feature selection method that selects whole categories of trajectory features gives comparable or better classification results than forward and backward selection, but the gains are not statistically significant.