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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 ...
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 ...
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 ...
OpenML: [493] Web platform with Python, R, Java, and other APIs for downloading hundreds of machine learning datasets, evaluating algorithms on datasets, and benchmarking algorithm performance against dozens of other algorithms. PMLB: [494] A large, curated repository of benchmark datasets for evaluating supervised machine learning algorithms ...
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 ...
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 ...
Keras is an open-source library that provides a Python interface for artificial neural networks.Keras was first independent software, then integrated into the TensorFlow library, and later supporting more.
First of all, a concept is a simple version of a Unified Modeling Language (UML) class. The class definition [1] is adopted to define a concept, namely: a set of objects that share the same attributes, operations, relations, and semantics. The following concept types are specified: STANDARD CONCEPT: a concept that contains no further (sub ...