Abstract: Optimization of nearest-neighbor feature selection depends on the number of samples and features, the type of statistical effect, the feature scoring algorithm, and class imbalance. We ...

Hann is a high-performance approximate nearest neighbor search (ANN) library for Go. It provides a collection of index data structures for efficient similarity search in high-dimensional spaces.

KAT is a suite of tools that analyse jellyfish hashes or sequence files (fasta or fastq) using kmer counts. The following tools are currently available in KAT: kmer: Produces a k-mer hash containing ...

Lower-income households are increasingly doing their shopping at discount stores, says Bank of America. Tuesday's lackluster retail-sales report alarmed some on Wall Street about the state of the U.S.

Dealing with high-dimensional data is a well-known limitation for the classic K-Nearest Neighbors (KNN) algorithm, creating substantial computational and memory overhead. While Quantum Machine ...