concept learningThe iterated version space algorithm (IVSA) has been designed and implemented to learn disjunctive concepts that have multiple classes. Unlike a traditional version space algorithm, IVSA first l
One far-reaching goal is that the AI algorithm after it is trained on a benchmark dataset will contain the reasoning abilities necessary to be able to use them in a real-world dataset.65 Particularly in CLEVER_HYP,64 it is clearly stated that it is created to test the reasoning skills th...
Repository for the AdaptiveRandomForest algorithm implemented in MOA 2016-04 random-forestclassificationensembleensemble-learningdecision-treesconcept-driftmoadatastream UpdatedOct 18, 2017 Java concept drift datasets edited to work with scikit-multiflow directly ...
Our approach is based on both refinement operator in inductive logic programming and reinforcement learning algorithm. The use of reinforcement learning significantly reduces the search space of candidate concepts. Besides, we present an experimental evaluation of constructing a family ontology. The results...
One view is that conceptual knowledge is organized using the circuitry in the medial temporal lobe (MTL) that supports spatial processing and navigation. In contrast, we find that a domain-general learning algorithm explains key findings in both spatial and conceptual domains. When the clustering mo...
Fig. 7 Algorithm 2—The learning process with explicit drift detection Full size image Samples from the current window/buffer are applied to each model in the repository to find the matching one. The match_percentage and the error measures described in the above section are computed. This proced...
In practice, however, concepts start reappearing, and since the algorithm does not need to recompute them, the overall computational complexity increases less. The actual increase per depth level depends, for example, on the internal consistency of the starting concept. The script outputs a ...
± 1.1% at baseline, and mean diabetes duration was 12.0 ± 8.9 years (Fig.6a). All inpatients underwent 5 d of intervention by AI. Over the trial, 90.2% of the AI recommendations were adopted by physicians, indicating a high level of confidence in the algorithm’s ...
(29), Steps 2–18 in Algorithm 2 are to compute the lower and upper approximations of the object set X0. Furthermore, Steps 19–24 are to find an exact or two approximate cognitive concepts for X0 as well as the learning accuracy α(X0). What is more, it is easy to check that ...
While the former may result in decreased performance on the main task due to the interpretability constraint, the latter can explain any machine learning algorithm (including better-than-human networks [1], [3], [5]) without altering the original performance. Several post-hoc techniques [6], ...