The proposed approach, named Explanation by Local Approximation (ELA), is simple and model agnostic: it finds the nearest neighbors of the point we want to explain and performs a linear regression using this subset of points. The coefficients of this linear regression are then used to generate ...
Table 2 McDonald’s omega coefficients for each country Full size table Results Descriptive statistics Table 3 reports the frequency of positive and negative emotions for men and women for each country. On an average, 26% of individuals across countries scored very low on positive emotions (2 or...
Furthermore, the linear models obtained from slise are sparse, meaning that the model coefficients are easier to interpret, especially for datasets with many attributes. Example 1: Robust Regression. Figure 1 shows a dataset containing outliers in the top left corner. Here ordinary least-squares ...
Regression analyses In Fig. 3, the results of the PRO-related coefficients are displayed based on three different models (admission PRO values, 12-month PRO values and PRO-change values), while controlling for other patient and treatment characteristics. The baseline model examines the association ...
In this study, we use Shapley values in a subtly different way: Instead of explaining what a single model “has learned”, we ask how much “can be learned” from a range of possible predictors. The results can be understood like the coefficients of a multiple linear regression, but ...
The adjusted determination coefficients in (Table 4) shows that correlated variables in the regression should be removed by an additional dimensionality reduction, further motivating our pooling of the feature maps. The large size of the ROP dataset, however, seems to lead to smaller difference ...
(Note: block lines represent statistically significant relationships; dashed lines represent statistically non-significant relationships. Beta weights (standardised regression coefficients) represent the strength of relationship between variables, with positive numbers indicating positive relationships and vice versa...
In order to use SLISE you need to have your data in a numerical matrix (or something that can be cast to a matrix), and the response as a numerical vector. Below is an example of SLISE being used for robust regression: library(slise) library(ggplot2) set.seed(42)x<-seq(-1,1,...
of characteristic periods and amplitudes (Fig.2). In particular, half-cycle periods (estimated by the first minimum of the Autocorrelation Function, ACF) cluster around 500 years (Fig.2b,c). Typical coefficients of variance (CV), a measure of oscillation amplitude, are 0.25 or more (Fig.2d...
Pearson correlation coefficients, independent t-test, one-way analysis of variance and multiple linear regression model were used to analyze the data. Results The average total score of sexual self-care in reproductive age women participating in the research was 70.66% ± 12.52%. In ...