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A faulty generalization is an informal fallacy wherein a conclusion is drawn about all or many instances of a phenomenon on the basis of one or a few instances of that phenomenon. It is similar to a proof by example in mathematics. [1] It is an example of jumping to conclusions. [2] For example, one may generalize about all people or all ...
Universal generalization / instantiation. Existential generalization / instantiation. In predicate logic, generalization (also universal generalization, universal introduction, [1][2][3] GEN, UG) is a valid inference rule. It states that if has been derived, then can be derived.
The universal law of generalization is a theory of cognition stating that the probability of a response to one stimulus being generalized to another is a function of the “distance” between the two stimuli in a psychological space. It was introduced in 1987 by Roger N. Shepard, [1] [2] who began researching mechanisms of generalization while ...
The problem of induction is a philosophical problem that questions the rationality of predictions about unobserved things based on previous observations. These inferences from the observed to the unobserved are known as "inductive inferences". David Hume, who first formulated the problem in 1739, [1] argued that there is no non-circular way to ...
For supervised learning applications in machine learning and statistical learning theory, generalization error[1] (also known as the out-of-sample error[2] or the risk) is a measure of how accurately an algorithm is able to predict outcome values for previously unseen data. Because learning algorithms are evaluated on finite samples, the ...
The statistical syllogism was used by Donald Cary Williams and David Stove in their attempt to give a logical solution to the problem of induction. They put forward the argument, which has the form of a statistical syllogism: The great majority of large samples of a population approximately match the population (in proportion) This is a large ...
Generalization is the concept that humans, other animals, and artificial neural networks use past learning in present situations of learning if the conditions in the situations are regarded as similar. [1] The learner uses generalized patterns, principles, and other similarities between past experiences and novel experiences to more efficiently ...
Spontaneous recovery. Spontaneous recovery is a phenomenon of learning and memory that was first named and described by Ivan Pavlov in his studies of classical (Pavlovian) conditioning. In that context, it refers to the re-emergence of a previously extinguished conditioned response after a delay. [1]