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In Java, this will mean that the method in the derived class will implicitly override the method in the base class, even though that may not be the intent of the designers of either class. To mitigate this, C# requires that if a method is intended to override an inherited method, the override keyword must be specified. Otherwise, the method ...
In object-oriented programming, a covariant return type of a method is one that can be replaced by a "narrower" (derived) type when the method is overridden in a subclass. A notable language in which this is a fairly common paradigm is C++. C# supports return type covariance as of version 9.0. [1]
When overriding one method with another, the signatures of the two methods must be identical (and with same visibility). In C#, class methods, indexers, properties and events can all be overridden. Non-virtual or static methods cannot be overridden. The overridden base method must be virtual, abstract, or override.
In some programming languages, function overloading or method overloading is the ability to create multiple functions of the same name with different implementations. Calls to an overloaded function will run a specific implementation of that function appropriate to the context of the call, allowing one function call to perform different tasks ...
Alternatively, the Fluent plugin allows calling any static method as an extension method without using annotations, as long as the method signature matches. In Smalltalk, any code can add a method to any class at any time, by sending a method creation message (such as methodsFor: ) to the class the user wants to extend.
The next iterate of a linear multistep method depends on the previous s iterates. Thus, in the definition for the local truncation error, it is now assumed that the previous s iterates all correspond to the exact solution:
In the standard form of the equation (see later in article), and are respectively replaced by / and ; the advantage of this being that and have some understandable physical meaning, as they represent an integration time and a derivative time respectively.
which for the logistic activation function = = (()) = This is the reason why backpropagation requires that the activation function be differentiable. (Nevertheless, the ReLU activation function, which is non-differentiable at 0, has become quite popular, e.g. in AlexNet)