Using a case study on human classification scenario, Costa et al. (2013) proposed an active learning framework which allows non-expert classification performed by crowds.
After a suite of reasonable test, this method can recognize traffic state all-day in real-time, and the classification of the method can achieve a higher coincide ratio with human classification.
Human classification of diagnoses is a labor intensive process that consumes significant resources.
Based on Bloom's Taxonomy, a human cognition classification, the Taxonomy Alignment for Gaming was devised by Allen Interactions, an instructional design company, to align game mechanics with specific performance objectives -- a framework that we align our work with at The Game Agency.
We highlight that SVM and NN perform best, but they do not provide a human readable classification model as rule-based classifiers, which permit to identify the different taxon specific k-mers.
The analysis of results on synthetic and real datasets shows that SVM and Naïve Bayes outperform on average the other considered classifiers, although they do not provide a human interpretable classification model.
The aim of this part of the research was to verify that such a tool is able to account for the human classification activity, which is important for potential applications.
The oversimplification with categorization into conscious and unconscious was eliminated in the last human classification; however recognition of impairment remained an important point [ 1].
Cutler et al. [87] presented a self-similarity-based time-frequency technology to detect and analyze periodic motion for human classification.
