When.com Web Search

Search results

  1. Results From The WOW.Com Content Network
  2. Constrained conditional model - Wikipedia

    en.wikipedia.org/wiki/Constrained_conditional_model

    Constrained conditional models form a learning and inference framework that augments the learning of conditional (probabilistic or discriminative) models with declarative constraints (written, for example, using a first-order representation) as a way to support decisions in an expressive output space while maintaining modularity and ...

  3. Constructive alignment - Wikipedia

    en.wikipedia.org/wiki/Constructive_alignment

    Constructive alignment is the underpinning concept behind the current requirements for programme specification, declarations of learning outcomes (LOs) and assessment criteria, and the use of criterion based assessment. There are two basic concepts behind constructive alignment: Learners construct meaning from what they do to learn.

  4. Cognitive categorization - Wikipedia

    en.wikipedia.org/wiki/Cognitive_categorization

    Categorization is a type of cognition involving conceptual differentiation between characteristics of conscious experience, such as objects, events, or ideas.It involves the abstraction and differentiation of aspects of experience by sorting and distinguishing between groupings, through classification or typification [1] [2] on the basis of traits, features, similarities or other criteria that ...

  5. Concept learning - Wikipedia

    en.wikipedia.org/wiki/Concept_learning

    Abstract-concept learning is seeing the comparison of the stimuli based on a rule (e.g., identity, difference, oddity, greater than, addition, subtraction) and when it is a novel stimulus. [9] With abstract-concept learning have three criteria’s to rule out any alternative explanations to define the novelty of the stimuli.

  6. Decision tree learning - Wikipedia

    en.wikipedia.org/wiki/Decision_tree_learning

    The problem of learning an optimal decision tree is known to be NP-complete under several aspects of optimality and even for simple concepts. [34] [35] Consequently, practical decision-tree learning algorithms are based on heuristics such as the greedy algorithm where locally optimal decisions are made at each node. Such algorithms cannot ...

  7. Constraint satisfaction problem - Wikipedia

    en.wikipedia.org/wiki/Constraint_satisfaction...

    Constraint learning infers and saves new constraints that can be later used to avoid part of the search. Look-ahead is also often used in backtracking to attempt to foresee the effects of choosing a variable or a value, thus sometimes determining in advance when a subproblem is satisfiable or unsatisfiable.

  8. Word learning biases - Wikipedia

    en.wikipedia.org/wiki/Word_learning_biases

    It is unclear if the word-learning constraints are specific to the domain of language, or if they apply to other cognitive domains. Evidence suggests that the whole object assumption is a result of an object's tangibility; children assume a label refers to a whole object because the object is more salient than its properties or functions. [7]

  9. Conditions of Learning - Wikipedia

    en.wikipedia.org/wiki/Conditions_of_Learning

    Different internal and external conditions are necessary for each type of learning. For example, for cognitive strategies to be learned, there must be a chance to practice developing new solutions to problems; to learn attitudes, the learner must be exposed to a credible role model or persuasive arguments.