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Although many authors generated comprehensible models from individual networks, much less work has been done in the explanation of ensembles.
In general, kinetic models are developed as comprehensible models, which accurately describe the metabolic process or receptor binding, but are usually simplified to yield workable models that are able to quantify a parameter of interest.
Linear models are a feasible tool for large-scale classification and regression tasks such as linear support vector machines (linear SVM) and logistic regression which provide comprehensible models for these tasks.
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The algorithm produces IF-THEN ordered rule list to learn a comprehensible model which can easily be verified by experts.
PNSRL enables the development of a more comprehensible model to calculate SRL and treats the system as a flow of interoperability.
There are many areas of application where a comprehensible model is fundamental to its proper use.
Moreover, having a comprehensible model of how the healthier behaviour would affect weight loss was also seen as useful.
These studies present an ideal example of how MD simulations can provide structural information that is not accessible by experiments and how MSMs can help reduce the complex conformational space exhibited in IDPs into simpler, human-comprehensible models.
Given the appropriate degrees of freedom that describe rate-limiting protein motions (i.e., reaction coordinates), an energy landscape reduces the complexity of protein motions into a simpler human-comprehensible model.
Extracting comprehensible genic models from this sea of data depends upon the identification of intron/exon boundaries.
The algorithm produces IF THEN ordered rule list and thus offer comprehensible classification model.
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