The simplest form of regression in Python is, well, simple linear regression. With simple linear regression, you're trying to ...

Splines Splines facilitate modelling non-linear relationships by splitting a continuous independent variable into intervals and fitting piecewise polynomial functions in each interval, which are ...

Thus, understanding the optimal intake of dietary fiber and its implications for cognitive function warrants further exploration, particularly under the hypothesis of a non-linear J-shaped ...

The paper is concerned with developing a production theory for the case when some inputs have nonlinear prices because the price depends on endogenous quality. This involves extending the notion of a ...

Activation functions play a critical role in AI inference, helping to ferret out nonlinear behaviors in AI models. This makes them an integral part of any neural network, but nonlinear functions can ...

This project simulates an experiment using Adaptive Random Fourier Features Kernel Least Mean Squares (ARFF-KLMS) to approximate non-linear functions. The algorithm adapts kernel bandwidth online, ...

Multivariate regression analysis was used to evaluate the relationship between alcohol intake and cognitive function. Smooth curve fitting and threshold effect analysis were employed to explore ...

We present and benchmark quantum computing approaches for calculating real-time single-particle Green’s functions and nonlinear susceptibilities of Hamiltonian systems. The approaches leverage ...

Computation of non-linear functions such as hyperbolic tangent and sigmoid is critical in machine learning. Furthermore, precision requirement varies across different layers in deep neural networks.