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Learning Object Metadata is a data model, usually encoded in XML, used to describe a learning object and similar digital resources used to support learning. The purpose of learning object metadata is to support the reusability of learning objects, to aid discoverability , and to facilitate their interoperability, usually in the context of ...
It provides a means to associate metadata with a class where the language does not have explicit support for such metadata. To use this pattern, a class implements a marker interface [ 1 ] (also called tagging interface ) which is an empty interface, [ 2 ] and methods that interact with instances of that class test for the existence of the ...
One of the key issues in using learning objects is their identification by search engines or content management systems. [13] This is usually facilitated by assigning descriptive learning object metadata. Just as a book in a library has a record in the card catalog, learning objects must also be tagged with metadata. The most important pieces ...
Meta-learning [1] [2] is a subfield of machine learning where automatic learning algorithms are applied to metadata about machine learning experiments. As of 2017, the term had not found a standard interpretation, however the main goal is to use such metadata to understand how automatic learning can become flexible in solving learning problems, hence to improve the performance of existing ...
The Semantic Web object-oriented model is more dynamic than most standard object systems, and is consistent with runtime metaobject protocols. For example, in the Semantic Web model classes are expected to change their relations to each other and there is a special inference engine known as a classifier that can validate and analyze evolving ...
It is an open-source cross-platform integrated development environment (IDE) for scientific programming in the Python language.Spyder integrates with a number of prominent packages in the scientific Python stack, including NumPy, SciPy, Matplotlib, pandas, IPython, SymPy and Cython, as well as other open-source software.
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...
In object oriented programming, objects provide a layer which can be used to separate internal from external code and implement abstraction and encapsulation. External code can only use an object by calling a specific instance method with a certain set of input parameters, reading an instance variable, or writing to an instance variable.