Package: faissR 0.99.13

faissR: FAISS-Backed Nearest Neighbours, Graph Clustering, kNN Models, and k-Means

Native nearest-neighbour search, graph construction, graph clustering, k-nearest neighbour prediction, and k-means helpers for large dimensionality reduction workflows in high-throughput biological data analysis, including single-cell, flow cytometry, imaging, and mass spectrometry applications. The package requires the FAISS C++ library for all builds, including CPU-only indexes, and can optionally use FAISS GPU indexes with NVIDIA cuVS integration or direct RAPIDS cuVS/CUDA indexes on NVIDIA machines. CPU-only systems do not need NVIDIA libraries, but NVIDIA CUDA/cuVS libraries are mandatory when a GPU-enabled build is explicitly requested. Supervised kNN models use knn(Xtrain, Ytrain) and predict(), or knn(Xtrain, Ytrain, Xtest) for immediate prediction. Class probabilities are returned through predict(type = "prob") for kNN classification models.

Authors:Stefano Cacciatore [aut, cre]