The classification of a scenario is performed by comparing a partial matching of its graph with graphs of positive and negative examples. We illustrate machine learning of graph structures using the Nearest Neighbor approach and then proceed to JSM-based concept learning, which minimizes the number ...
Discover 10+ inspiring concept map examples with free templates. Learn how to create, structure, and use concept maps for brainstorming, learning and business.
Authentic learning activities take class material into the real world. Learn about the concept and value of authentic learning activities, explore the basic tenets of authentic learning activities, and take a look at a few examples. Authentic Learning Activities Do you remember taking a class and ...
These examples demonstrate why it is essential to learn the original classification criteria when solving concept hierarchy refinement problems. The above analysis suggests that a learning-based (or supervised) approach might be more suitable for concept hierarchy refinement. One plausible way would be ...
■PAC-learningCGs[Jappy&Nock] ■SizeofCGclassandgeneralization (projection)operatorpolynomialin ■Numberofrelations ■Numberofconcepts ■Numberoflabels FLAIRS20015 GaloisLattice FLAIRS20016 ■Eachnodeconsistsofadescription graphandsetofsubsumedexamples ■Beginswithpositiveexamples ■Generalizationoperator ■Mostspecif...
Fig. 1: Cluster learning applied to conceptual and spatial examples. aThe most similar cluster moves (i.e., adjusts its tuning) toward its newest member and becomes associated with a response (blue for bird, red for mammal).bOut of a pool of many randomly tuned clusters, a subset comes ...
which would mean that this is not a foo. We haven't seen enough examples to know which model is correct, though, so we're having trouble settling in to a level of specialization or generalization. That will be the main topic of this lesson: how to use new examples to help specialize ...
This paper introduces a logical model of inductive generalization, and specifically of the machine learning task of inductive concept learning (ICL). We argue that some inductive processes, like ICL, can be seen as a form of defeasible reasoning. We define a consequence relation characterizing whic...
Towards a Knowledge-Based Framework for Agents Interacting in the Semantic Web A multi-agent system was extended with defeasible reasoning and a reusable agent model is proposed for customizable agents, equipped with a knowledge base ... K Kravari,E Kontopoulos,N Bassiliades - ACM 被引量: 21...
Vos, H. J. (2007): A Bayesian sequential procedure for determining the optimal number of interrogatory examples for concept-learning, Computers in Human Behavior 23 (1), 609- 627.Vos, H. J. (2007). A Bayesian sequential procedure for determining the optimal number of interrogatory examples...