Visualization of Regression Models Using visreg

CFD Data Reduction for Indoor Environments: Use of Statistical (Linear Regression) and Neural (Back-propagation) models

1.0 ABSTRACT Dynamic data visualization in real-time involves rapid simulations of computerized models. Although computing power has increased exponentially in the last few decades, detailed simulations using software introduce time-delay that defeat the notion of realtime data visualization of the generated results. Approximate techniques can pave way for efficient generation of continuous flo...

Visualization of Regression Models Using Discriminative Dimensionality Reduction

Although regression models offer a standard tool in machine learning, there exist barely possibilities to inspect a trained model which go beyond plotting the prediction against single features. In this contribution, we propose a general framework to visualize a trained regression model together with the training data in two dimensions. For this purpose, we rely on modern nonlinear dimensionali...

Residual Generation and Visualization for Understanding Novel Process Conditions

We study the generation and visualization of residuals for detecting and identifying unseen faults using autoassociative models learned from process data. Least squares and kernel regression models are compared on the basis of their ability to describe the support of the data. Theoretical results show that kernel regression models are more appropriate in this sense. Moreover, experiments on vib...

Estimation of Variance Components for Body Weight of Moghani Sheep Using B-Spline Random Regression Models

The aim of the present study was the estimation of (co) variance components and genetic parameters for body weight of Moghani sheep, using random regression models based on B-Splines functions. The data set included 9165 body weight records from 60 to 360 days of age from 2811 Moghani sheep, collected between 1994 to 2013 from Jafar-Abad Animal Research and Breeding Institute, Ardabil province,...

The relationships between grain yield of spring wheat and rainfall distribution in western australia using regression models