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One of the issues with QSAR models is their poor interpretability.
Research has been undertaken to mitigate this 'black box' issue of poor interpretability and trends in the literature are discussed here.
These black box models (models with poor interpretability) will generally perform better on complex problems in comparison to white-box models (models with good interpretability) such as Decision Trees (DT) or Linear Regression (LR).
This results in poor interpretability and the failure to unearth subtle informative variation.
If one basis vector was allocated to handle this trend, good fits were obtained but poor interpretability.
High correlation among multiple variables in a regression model, referred to as multicollinearity, leads to poor interpretability of multiple regression slopes [ 48].
Similar(51)
The analysis of thousands of measurements often leads to results with poor biological interpretability and plausibility.
And such discussions are fueled by recent advances in deep learning experimentations and applications, which are however often plagued by its craftiness, un-interpretability, and poor generalizability.
Poor patient retention threatens the scientific integrity of the study and the interpretability of data and has been widely recognized as a challenge in long-term studies (17).
Further study is needed of how methodological artifacts (e.g., study area size, availability, and comparability of GIS data, or monitoring methods), interpretability of covariates, and differences in pollution source or dispersion characteristics contribute to poor transferability.
Although the overall model reflected the complex interrelationship of the built environment, the social environment, psychological distress, and physical functioning, we conducted a final series of supplementary analyses to gain additional depth and practical interpretability for the effect of a negative built environment as a predictor of poor physical functioning.
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