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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.
[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 ...
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 ...
An argument map typically includes all the key components of the argument, traditionally called the conclusion and the premises, also called contention and reasons. [1] Argument maps can also show co-premises, objections, counterarguments, rebuttals, inferences, and lemmas. There are different styles of argument map but they are often ...
The cognitive map is generated from a number of sources, both from the visual system and elsewhere. Much of the cognitive map is created through self-generated movement cues. Inputs from senses like vision, proprioception, olfaction, and hearing are all used to deduce a person's location within their environment as they move through it. This ...
A cognitive map is "a mental model of objects' spatial configuration that permits navigation along optimal path between arbitrary pairs of points." [16] This mental map is built upon two fundamental bedrocks: layout, also known as route knowledge, and landmark orientation. Layout is potentially the first method of navigation that people learn ...
Geometric feature learning is a technique combining machine learning and computer vision to solve visual tasks. The main goal of this method is to find a set of representative features of geometric form to represent an object by collecting geometric features from images and learning them using efficient machine learning methods.
For example: The X12 star system in the Andromeda nebula is like the Solar System. - This is a literal similarity, because the intention is to map both relationships (e.g. between planets and the Sun) and attributes (e.g. the size and temperature of the Sun) The hydrogen atom is like the Solar System. (Rutherford, 1906) - This is an analogy ...
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