GitHub

AKDE: Multivariate Adaptive Kernel Density Estimation Using Gaussian Mixture Model

AKDE provides an accurate, adaptive kernel density estimator based on the Gaussian Mixture Model for multidimensional data. This Python implementation includes automatic grid construction for ...
Frontiers

Kernel Density Estimation of Electromyographic Signals and Ensemble Learning for Highly Accurate Classification of a Large Set of Hand/Wrist Motions

The performance of myoelectric control highly depends on the features extracted from surface electromyographic (sEMG) signals. We propose three new sEMG features based on the kernel density estimation ...
Frontiers

Probabilistic Optimal Power Flow Calculation Method Based on Adaptive Diffusion Kernel Density Estimation

1 School of Electrical Engineering, Northeast Electric Power University, Jilin City, China 2 China Electric Power Research Institute, Nanjing, China To accurately evaluate the influence of the ...
Scientific Research Publishing

Bayesian Classifier Based on Robust Kernel Density Estimation and Harris Hawks Optimisation ()

In real-world applications, datasets frequently contain outliers, which can hinder the generalization ability of machine learning models. Bayesian classifiers, a popular supervised learning method, ...