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The method used to design the intelligent system has been the ID3, which is able to generate a minimal decision tree.
The algorithms use simple flow pathways with minimal decision points.
These are rules selected from the set of all minimal decision rules induced from information table processed by DRSA.
In the rough set-based machine learning a set of minimal decision IF-THEN rules is inferred from a number of labelled examples.
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Minimal cost decision tree construction plays a crucial role in cost sensitive learning.
The objective of this study was to describe, from the perspective of experienced EHR users, the transition from an older, locally developed EHR with minimal clinical decision support (CDS) for e-prescribing to a newer, commercial EHR with more robust CDS for e-prescribing.
In a setting like rural Mozambique where education is free and therefore pecuniary costs of education are minimal, the decision to send a child to school may be less related to a family's ability to incur such costs and more associated with the opportunity cost of children's time and the perceived returns from children's education.
The ASP aimed to curtail unnecessary use by engaging the prescriber in frequent, scheduled, face-to-face clinical-decision support, in the setting of minimal electronic decision-support tool availability.
As there are no objective and compelled rules for determination of an optimal cluster number we used 3 criteria: the development of values of the WARD fusion algorithm with respect to cluster numbers, practical decisions about minimal group numbers and decisions about sense of combining groups as regards content.
The algorithms contain a minimal number of decision points.
The scales range from 0 to 100, whereby, a score of 100 indicates minimal job variety, decision latitude, social support, job security, job satisfaction, and high psychological and physical workloads or stress.
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