Self-interpreting regression models based on the least absolute shrinkage and selection operator (LASSO) excel in WPF. Therefore, it is crucial to explore their underlying decision logic and the practical implications of their coefficients to extract beneficial domain knowledge. An interpreting framework ...
In a one-tailed alternative: H0 is the same Ha: Bj < 0 The decision rule is: If tj* ≤ critical t-table value reject H0 Some General Remarks When reporting the results of a regression analysis, it is customary to report either the standard errors or the t-values in parenthesis below ...
Analyzing and interpreting the results of randomized experiments involves organizing data, and processing it with analytical tools according to the...
In summary, different DFT functionals may be used to perform a computer simulation but they must be chosen wisely depending on the property of interest because of their intrinsic limitations. By being based on first principles, DFT provides results at the electronic level, which is both a strengt...
In summary, different DFT functionals may be used to perform a computer simulation but they must be chosen wisely depending on the property of interest because of their intrinsic limitations. By being based on first principles, DFT provides results at the electronic level, which is both a strengt...
(e)-(f) use the regional representative types of core form representation analyzed in Fig. 8 for land use efficiency. Table 4. Regression results for the impact of distance to city center on land use efficiency. logyRaw formsAll core formsRegional representative forms logEarealogEnumlogEarealog...
Behav Res (2017) 49:394–402 DOI 10.3758/s13428-016-0785-2 Multicollinearity is a red herring in the search for moderator variables: A guide to interpreting moderated multiple regression models and a critique of Iacobucci, Schneider, Popovich, and Bakamitsos (2016) Gary H. McClelland1 & ...
Second, in the interpreting stage, we used GNNExplainer to interpret learned GAT2 model with feature importance. We experimentally compared GNNExplainer with two well-known interpretation methods including Saliency Map and DeepLIFT to interpret the learned model, and the results showed GNNExplainer ...
Results: In this paper, we propose a graph attention network based learning and interpreting method, namely GAT-LI, which learns to classify functional brain networks of ASD individuals versus healthy controls (HC), and interprets the learned graph model with feature importance. Specifically, ...
This in turn gives rise to a “significant” vs. “nonsignificant” results determination. Too often, that is the end of the road in a given study, and the authors draw conclusions on a substantive and complex issue from that p-value only. Usually, once an effect has been found, no ...