Local intrinsic dimensionality enables selection of query sets with varying difficulty for nearest neighbor search benchmarking, and common real-world datasets are not diverse as performance on one predicts others well.
In: 1st Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning (EDML 2019) (2019), https://imada.sdu.dk/Research/EDML/
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The Role of Local Intrinsic Dimensionality in Benchmarking Nearest Neighbor Search
Local intrinsic dimensionality enables selection of query sets with varying difficulty for nearest neighbor search benchmarking, and common real-world datasets are not diverse as performance on one predicts others well.