Logistic regression is a tool used in data science and machine learning to predict binary outcomes. Applications range from ...

Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math ...

DistPred, a novel method for regression and forecasting tasks that can estimate ... DistPred achieves state-of-the-art performance on multiple datasets while significantly improving computational ...

In both sets of experiments, the 128-element linear array ... the Gaussian process regression models predicted level ground and ramp ambulation kinematics with greater accuracy in comparison to stair ...