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  2. Transduction (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Transduction_(machine...

    The most well-known example of a case-bases learning algorithm is the k-nearest neighbor algorithm, which is related to transductive learning algorithms. [2] Another example of an algorithm in this category is the Transductive Support Vector Machine (TSVM). A third possible motivation of transduction arises through the need to approximate.

  3. Piaget's theory of cognitive development - Wikipedia

    en.wikipedia.org/wiki/Piaget's_theory_of...

    [39] [44] Unlike deductive or inductive reasoning (general to specific, or specific to general), transductive reasoning refers to when a child reasons from specific to specific, drawing a relationship between two separate events that are otherwise unrelated. For example, if a child hears the dog bark and then a balloon popped, the child would ...

  4. Transduction (psychology) - Wikipedia

    en.wikipedia.org/wiki/Transduction_(psychology)

    The etymological origin of the word transduction has been attested since the 17th century (during the flourishing of Neo-Latin, Latin vocabulary words used in scholarly and scientific contexts [3]) from the Latin noun transductionem, derived from transducere/traducere [4] "to change over, convert," a verb which itself originally meant "to lead along or across, transfer," from trans- "across ...

  5. Support vector machine - Wikipedia

    en.wikipedia.org/wiki/Support_vector_machine

    Transductive support vector machines extend SVMs in that they could also treat partially labeled data in semi-supervised learning by following the principles of transduction. Here, in addition to the training set D {\displaystyle {\mathcal {D}}} , the learner is also given a set

  6. Fluid and crystallized intelligence - Wikipedia

    en.wikipedia.org/wiki/Fluid_and_crystallized...

    Fluid intelligence is the ability to solve novel reasoning problems and is correlated with a number of important skills such as comprehension, problem-solving, and learning. [4] Crystallized intelligence, on the other hand, involves the ability to deduce secondary relational abstractions by applying previously learned primary relational ...

  7. Logical reasoning - Wikipedia

    en.wikipedia.org/wiki/Logical_reasoning

    Logical reasoning is a form of thinking that is concerned with arriving at a conclusion in a rigorous way. [1] This happens in the form of inferences by transforming the information present in a set of premises to reach a conclusion.

  8. Weak supervision - Wikipedia

    en.wikipedia.org/wiki/Weak_supervision

    The transductive learning framework was formally introduced by Vladimir Vapnik in the 1970s. [6] Interest in inductive learning using generative models also began in the 1970s. A probably approximately correct learning bound for semi-supervised learning of a Gaussian mixture was demonstrated by Ratsaby and Venkatesh in 1995.

  9. Epistemic modal logic - Wikipedia

    en.wikipedia.org/wiki/Epistemic_modal_logic

    Epistemic modal logic is a subfield of modal logic that is concerned with reasoning about knowledge.While epistemology has a long philosophical tradition dating back to Ancient Greece, epistemic logic is a much more recent development with applications in many fields, including philosophy, theoretical computer science, artificial intelligence, economics, and linguistics.

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