Header-only C++ HNSW implementation with python bindings, insertions and updates. init_index(max_elements, M = 16, ef_construction = 200, random_seed = 100, allow_replace_deleted = False) initializes ...

The graphtools.Graph class provides an all-in-one interface for k-nearest neighbors, mutual nearest neighbors, exact (pairwise distances) and landmark graphs. Use it as follows: from sklearn import ...

Machine learning is rapidly emerging as one of the most transformative technologies in the digital age. It combines the principles of computer science, statistics, and data analysis to develop ...

Chemistry Teaching Laboratory, Department of Chemistry, University of Oxford, Oxford, United Kingdom of Great Britain and Northern Ireland, OX1 3PS ...

Classification is a data mining technique used to predict the class or category of a given object based on its attributes. It is a type of supervised learning, where the algorithm learns from a ...

A k-nearest neighbors is algorithm used for classification and regression. It classifies a new data point by finding the k-nearest points in the training dataset and assigns it the majority class ...

While neural networks used in practice are often very deep, the benefit of depth is not well understood. Interestingly, it is known that increasing depth is often harmful for regression tasks. In this ...

Compound potency prediction is a popular application of machine learning in drug discovery, for which increasingly complex models are employed. The general aim is the identification of new chemical ...

Since 1992, all state-of-the-art methods for fast and sensitive identification of evolutionary, structural, and functional relations between proteins (also referred to as “homology detection”) use ...