(2021b) developed 6 ML models of long short-term memory (LSTM), K-nearest neighbors (KNN), deep neural networks (DNN), Gaussian ... combined with the Random Forest (RF) algorithm. Zhang et al. (2024) ...

Impact Statement: Traditional K-Nearest Neighbor (kNN) algorithms rely on real-number-based distance metrics, which can struggle to capture complex, nonlinear relationships between features in ...

Start the program using command line "python3 ocrlearnKnn.py". Write digits on a paper under the camera and check whether they are detected correctly. Training your own hand writing data: first, press ...

Our goal is to work together to document and model beautiful, helpful and interesting algorithms using code. We are an open-source community - anyone can contribute. We check each other's work, ...

The outcome provided a predictive framework for various heart diseases using decision tree, random forest, logistic regression, and KNN algorithms ... The Extra Tree model was implemented using a ...

The momentum CMA blind equalization updates the equalizer weights by Equation (7), which a momentum term adds to the updating formula of CMA. Adaptive momentum algorithms update the weights of ...