Sentence examples for a better interpretability from inspiring English sources

Another advantage of feature selection is a better interpretability of a classification model based on lesser features.

We therefore selected (M_{25}) for annotation, as this model has a better interpretability compared to (M_{14}) (more specific topics), with comparable quality of model fit (similar AIC).

This is contrary to other methods such as decision tree or regression, which have a better interpretability (and perform well on binary problems but do not allow non-linear separation).

To allow for a better interpretability of the results reached in those Cox regression analyses, for each of the two response variables (OS, DFS) only factors showing a p-value of ≤ 0.1 in the corresponding univariate log-rank analysis were incorporated as independent variables in the according Cox regression models.

A continuous age variable was used for all analyses; for better interpretability when displaying results, age was grouped into four categories with equal intervals: 7 to 9, 10 to 12, 13 to 15, and 16 to 18, corresponding roughly to elementary, elementary/early middle school, late middle school/early high school, and upper high school.

However, some advantages of CSM approach compared to ConMap and ConStat are i) a reduced set of scales that still manage to represent the entire extent of the range of scales, ii) a reduced set of attributes at each scale, iii) more efficient computation, and iv) better interpretability of the important covariates used in the modelling and thus of the factors that affect soil formation.

This algorithm has better interpretability like many other NMF-based methods.

This improves the power for detecting perturbations during the onset and the progression of comorbidity, and allows for better interpretability of the dynamics at different time spans.

Therefore, in this study an attempt has been made to determine geomorphological parameters and to study the intercorrelationship (multicollinearity) among variables to screen out the less significant variables out of the analysis and to arrange the remaining into physically significant groups by applying principal component analysis for better interpretability.

Factors were rotated using varimax rotation to achieve uncorrelated factors with better interpretability.

In order to obtain more realistic models with better interpretability, several classification models have been proposed.