GitHub

Hnswlib - fast approximate nearest neighbor search

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 ...
GitHub

Scikit-Learn compatible HMM and DTW based sequence machine learning algorithms in Python.

Sequentia is a Python package that provides various classification and regression algorithms for sequential data, including methods based on hidden Markov models and dynamic time warping. Some ...
Psychology Today

Brain-Computer Interfaces Boosted by Novel AI Algorithm

The rise of artificial intelligence (AI) deep learning algorithms is helping to accelerate brain-computer interfaces (BCIs). Published in this month’s Nature Neuroscience is new research that shows ...
IEEE

Implementation of ML Algorithm for Spyware Detection System Using SVM with KNN Algorithm for Comparison of Accuracy

Abstract: The research examines the Support Vector Machines (SVM) and K-Nearest Neighbor (KNN) machine learning algorithms with the goal of using machine learning to detect malware and mitigate ...
Frontiers

Causative Classification of Ischemic Stroke by the Machine Learning Algorithm Random Forests

Prognosis, recurrence rate, and secondary prevention strategies differ by different etiologies in acute ischemic stroke. However, identifying its cause is challenging. We retrospectively reviewed the ...
IEEE

Improving KNN Algorithm Efficiency Based on PCA and KD-tree

Abstract: K-nearest neighbor (KNN) algorithm is a simple and widely used classification method in machine learning. This algorithm tries to search every object in the dataset to find the nearest ...
Frontiers

deepMNN: Deep Learning-Based Single-Cell RNA Sequencing Data Batch Correction Using Mutual Nearest Neighbors

It is well recognized that batch effect in single-cell RNA sequencing (scRNA-seq) data remains a big challenge when integrating different datasets. Here, we proposed deepMNN, a novel deep ...