Nakashima, "Multiple regression with fuzzy data," Fuzzy Sets and Systems, vol. 158, no. 19, pp. 2169-2188, 2007.Bargiela, A.; Pedrycz, W.; Nakashima, T. Multiple regression with fuzzy data. Fuzzy Sets Syst. 2007, 158, 2169-2188. [CrossRef]...
Regression with the records having different weights. All of the other concepts in simple linear regression, such as fitting by least squares and the definition of fitted values and residuals, extend to the multiple linear regression setting. For example, the fitted values are given by: Y ^ i...
In this section, we apply our BMRKR (Bayesian Multiple Response Kernel Regression) model on two simulated data sets and two real near infra-red spectroscopy data sets. Data pre-processing: The two real data sets are (i) Biscuit dough data (Osborne et al., 1984) and (ii) Wheat Data (...
Rather than just providing you with a general guide to setting up your data, we show you how to do this for every statistical test in our site (i.e., the setup is different for a paired-samples t-test compared with a two-way ANOVA, or multiple regression, for example)....
Regression Data Sets This document describes some regression data sets available at LIACC. These data sets can be downloaded and they are provided in a format ready for use with the RT tree induction system. Through the use of some available scripts they can also be used with Cubist, Mars ...
If simply iterating all possible combinations of feature sets, the identification and quantification of the co-varying set of features will be computationally intractable for high-dimensional data. An efficient method is desired to first identify the set of features from multiple modalities that are ...
the CC analysis yields substantially different parameter estimates for multiple regression coefficients as well as disagreement in statistical significance or in direction of estimated effect for eight features. This demonstrates the need for adequate handling missing data in the analysis of the GCASR data...
Regression analysis. Regression analysis estimates and models the relationships between sets of variables. One example is examining the number of Facebook friends an author has and the number of hardcovers her last book sold to predict a different variable, such as the success of her forthcoming ...
Each class of error can require multiple data sets in order to validate that the ETL is programmed correctly. Consider the dirty data case, for example. The formatting errors itsubmitsto the ETL may well be caught when the data set is landed or at least during integration, but there will ...
These sampled cells are waypoints (multiple per cell type) that define clear structure in the neighbor graph; however, the cell states themselves remain somewhat diffuse (Fig. 1f). To refine metacells, we employ kernel archetypal analysis (Fig. 1g, Extended Data Fig. 1a and Methods). ...