# k-Nearest Neighbors

MEOW converts non-interactive 3D segmentation backbones into open-world interactive segmentation systems without updating any learnable parameters. Interactive segmentation had been confined to the open-set setting, able to predict or reject unknown structures but not to accumulate those predictions. MEOW pairs a frozen feature extractor with parameter-free transductive reasoning and memory consolidation, storing user-confirmed pseudo-labels in memory for later queries to retrieve; on classes never seen in training it keeps improving its own predictions as memory grows, and it transfers zero-shot to micro-CT and other imaging modalities.

MEOW converts non-interactive 3D segmentation backbones into open-world interactive segmentation systems without updating any learnable parameters. Interactive segmentation had been confined to the open-set setting, able to predict or reject unknown structures but not to accumulate those predictions. MEOW pairs a frozen feature extractor with parameter-free transductive reasoning and memory consolidation, storing user-confirmed pseudo-labels in memory for later queries to retrieve; on classes never seen in training it keeps improving its own predictions as memory grows, and it transfers zero-shot to micro-CT and other imaging modalities.

scCont breaks cell-state transitions in time-course single-cell RNA data into interpretable functional transition units: instead of explicit time labels or clustering priors, it selects positive pairs with a k-nearest-neighbor graph in expression space for contrastive learning, then uses Shapley attribution to map latent dimensions back to gene programs. Across four SERGIO simulated datasets and 13 epithelial-to-mesenchymal transition time-course datasets, its gene modules carry statistical filtering and GO enrichment annotation; on simulated data at k=10, background genes make up 7.0% of the 100 highest-attributed genes per latent, against a 73.3% chance level.

scCont breaks cell-state transitions in time-course single-cell RNA data into interpretable functional transition units: instead of explicit time labels or clustering priors, it selects positive pairs with a k-nearest-neighbor graph in expression space for contrastive learning, then uses Shapley attribution to map latent dimensions back to gene programs. Across four SERGIO simulated datasets and 13 epithelial-to-mesenchymal transition time-course datasets, its gene modules carry statistical filtering and GO enrichment annotation; on simulated data at k=10, background genes make up 7.0% of the 100 highest-attributed genes per latent, against a 73.3% chance level.

Under a nested cross-validation framework, this study compared seven hyperparameter tuning strategies for classical KNN over a mixed search space comprising an integer neighborhood size k, a categorical distance metric, and a continuous Minkowski exponent p—grid search, random search, Bayesian optimization, genetic algorithm, surrogate optimization, particle swarm optimization (PSO), and grey wolf optimizer—evaluating them on 15 public classification datasets using accuracy, macro AUC, cross-validation loss, cross-entropy loss, and runtime, and found that PSO achieved the best overall mean rank but held a statistically significant advantage only over random search under Holm-corrected Wilcoxon signed-rank tests.

Under a nested cross-validation framework, this study compared seven hyperparameter tuning strategies for classical KNN over a mixed search space comprising an integer neighborhood size k, a categorical distance metric, and a continuous Minkowski exponent p—grid search, random search, Bayesian optimization, genetic algorithm, surrogate optimization, particle swarm optimization (PSO), and grey wolf optimizer—evaluating them on 15 public classification datasets using accuracy, macro AUC, cross-validation loss, cross-entropy loss, and runtime, and found that PSO achieved the best overall mean rank but held a statistically significant advantage only over random search under Holm-corrected Wilcoxon signed-rank tests.