This paper proposes a learning-based image interpolation method based on weighted direct nonlinear regression. It attempts to learn the nonlinear relationship between the low-resolution patches and ...

Software effort estimation in the early stages of the software life cycle is one of the most essential and daunting tasks for project managers. In this research, a new model based on nonlinear ...

Nonlinear Regression: Estimating Hand-to-Camera Distance This project implements a quadratic nonlinear regression model to estimate the real-world distance between a hand and a camera based on the ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric ...

Using the boundaries of the intervals of the splines, we fit a smooth cubic interpolation function that goes through (n + 1) data points. On the other hand, polynomial regression is a useful technique ...

Covers areas such as Regularized Logistic Regression, Optimization, Kernel Methods, PageRank, Kernel PCA, Association Rule Mining, Anomaly Detection, Parametric/Nonparametric Nonlinear Regression, etc ...

Nonlinear regression is a form of regression analysis in which data fit to a model is expressed as a mathematical function.