概念学习(ConceptLearning)unexpectedendofjsoninput请尝试刷新页面或更换浏览器重试 概念学习( ConceptLearning) 1. 从特殊的训练样例中归纳出一般函数是机器学习的核心问题。一般函数是对理想目标函数的函数逼近(function approximation)。简而言之,从特殊到 普通。与此对应的是演绎推理(deductive reasoning),就是从一般性...
The purpose of this essay to evaluate the great thinker of Kazak Abai's thougts about learning of foreign languages e.t.c. Russian. For this reason Abai's life briefly is taken consideration and a special attention is given to his thougts about learning of foreign language.Key words: Abai...
The available concept-learners only partially fulfill the needs imposed by the learning apprentice generation of learners. We present a novel approach to i
Individual differences in information processing during concept learning Leonard I. Jacobson, Jim Millham, Stephen E. Berger Download PDF (359 KB) Abstract Information processing strategies of Ss differing in intelligence were evaluated. Ss of lowest intelligence were found to use the same proces...
This paper describes a concept formation approach to the discovery of new concepts and implication rules from data. This machine learning approach is based on the Galois lattice theory, and starts from a binary relation between a set of objects and a set of properties (descriptors) to build a...
(Designing a Concept-Based Curriculum in English Language Arts: Meeting the Common Core With Intellectual Integrity, K-12, 2013, Corwin);以及在萊絲莉‧勞德(Leslie Laud)主編的《科文精選:讀寫能力、數學與科學的差異化教學》(The Best of Corwin: Differentiated Instruction in Literacy, Math, and ...
Self-concept Enhancement and Learning Facilitation (SELF) Research Group, University of Oxford, UK * The first two authors (A.J.S.M and C.M.) contributed equally to this article and their order was determined at random: both should thus be considered first authors. This manuscript was ...
On-line learning in domains where the target concept depends on some hidden context poses serious problems. A changing context can induce changes in the target concepts, producing what is known as concept drift. We describe a family of learning algorithms that flexibly react to concept drift and...
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 show that our approach is competitive with an existing learning system for \\\(\\\ensuremath{\\\cal E}\\\...
is adopted to utilize unlabeled test examples to alleviate the low-resource learning problem. Experiments on two widely-used zero-shot compositional learning (ZSCL) benchmarks have demonstrated the effectiveness of the model compared with recent approaches on both conventional and generalized ZSCL setting...