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[a] More simply put, concepts are the mental categories that help us classify objects, events, or ideas, building on the understanding that each object, event, or idea has a set of common relevant features. Thus, concept learning is a strategy which requires a learner to compare and contrast groups or categories that contain concept-relevant ...
One-shot learning is an object categorization problem, found mostly in computer vision.Whereas most machine learning-based object categorization algorithms require training on hundreds or thousands of examples, one-shot learning aims to classify objects from one, or only a few, examples.
An object is therefore congruent to its mirror image (even if it is not symmetric), but not to a scaled version. Two congruent objects always have either the same shape or mirror image shapes, and have the same size. Objects that have the same shape or mirror image shapes are called geometrically similar, whether or not they have the same size ...
A learning object is "a collection of content items, practice items, and assessment items that are combined based on a single learning objective". [1] The term is credited to Wayne Hodgins, and dates from a working group in 1994 bearing the name. [2]
In machine learning, a linear classifier makes a classification decision for each object based on a linear combination of its features.Such classifiers work well for practical problems such as document classification, and more generally for problems with many variables (), reaching accuracy levels comparable to non-linear classifiers while taking less time to train and use.
Rain has seen children as young as 10 and others in their 70s take to the water. Although some come in groups, most are strangers who have grown to become friends or acquaintances over time, she said.
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