In this study we present a method for improving the generalization ability of RBF neural network by using a statistics linear regression technique based on the OLS algorithm. We first discuss a modified way to determine the center and width of the hidden layer neurons. Then, substituting the QR...
PACF can be explained using a linear regression where we predict y(t) from y(t-1), y(t-2), and y(t-3) [2]. In PACF, we correlate the “parts” of y(t) and y(t-3) that are not predicted by y(t-1) and y(t-2). ...
To create a model that offers simplicity and interpretability, we used a linear regression model53. In addition to being useful for analyzing direct relationships between variables, linear regression can be utilized to assess the complexity of other models. To identify complex nonlinear correlations ...
Get an introduction to PyTorch, then learn how to use it for a simple problem like linear regression — and a simple way to containerize your application.
The app creates a plot of the response with the record number on thex-axis. Create a selection of linear models. On theLearntab, in theModelssection, click the arrow to open the gallery. In theLinear Regression Modelsgroup, clickLinear. ...
Linear regression, also known as simple linear regression or bivariate linear regression, is used when we want to predict the value of a dependent variable based on the value of an independent variable. For example, you could use linear regression to understand whether exam performance can be ...
When a dependent variable is categorical, the ordinary least squares (OLS) method can no longer produce the best linear unbiased estimator (BLUE); that is, OLS is biased and inefficient. Consequently, researchers have developed various regression models for categorical dependent variables. The ...
disturbed by noise data.The least-absolute criteria can overcome the drawbacks of least-square criteria,but how to design and implement a regression algorithm based on it is a difficult problem.In this paper,a least-absolute regression algorithm using linear programming is proposed and realized by ...
Identifying pathogenic variants from the vast majority of nucleotide variation remains a challenge. We present a method named Multimodal Annotation Generated Pathogenic Impact Evaluator (MAGPIE) that predicts the pathogenicity of multi-type variants. MAG
An unbiased test for the appropriateness of the simple linear regression model is presented. The null hypothesis is that the underlying regression function is indeed a line, and the alternative is that it is convex. The exact distribution for a likelihood ratio test statistic is that of a mixtur...