Search results
Results from the WOW.Com Content Network
The first Java GUI toolkit was the Abstract Window Toolkit (AWT), introduced with Java Development Kit (JDK) 1.0 as one component of Sun Microsystems' Java platform. The original AWT was a simple Java wrapper library around native (operating system-supplied) widgets such as menus, windows, and buttons.
Where there is a Swing version of an AWT component it will begin with J- and should be used exclusively, replacing the AWT version. For example, in Swing, only use JButton, never Button class. As mentioned above, the AWT core classes, such as Color and Font, are still used as-is in Swing. When drawing in Swing, use JPanel and override ...
The "Java Foundation Classes" were later renamed "Swing", adding the capability for a pluggable look and feel of the widgets. This allowed Swing programs to maintain a platform-independent code base, but mimic the look of a native application. The release of JFC made IFC obsolete, and dropped interest for Microsoft's AFC.
Swing is a highly modular-based architecture, which allows for the "plugging" of various custom implementations of specified framework interfaces: Users can provide their own custom implementation(s) of these components to override the default implementations using Java's inheritance mechanism via LookAndFeel.
In information science, formal concept analysis (FCA) is a principled way of deriving a concept hierarchy or formal ontology from a collection of objects and their properties. Each concept in the hierarchy represents the objects sharing some set of properties; and each sub-concept in the hierarchy represents a subset of the objects (as well as ...
Model selection is the task of selecting a model from among various candidates on the basis of performance criterion to choose the best one. [1] In the context of machine learning and more generally statistical analysis, this may be the selection of a statistical model from a set of candidate models, given data.
It is a main task of exploratory data analysis, and a common technique for statistical data analysis, used in many fields, including pattern recognition, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine learning. Cluster analysis refers to a family of algorithms and tasks rather than one ...
Learning to rank [1] or machine-learned ranking (MLR) is the application of machine learning, typically supervised, semi-supervised or reinforcement learning, in the construction of ranking models for information retrieval systems. [2] Training data may, for example, consist of lists of items with some partial order specified between items in ...