enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Argument-dependent name lookup - Wikipedia

    en.wikipedia.org/wiki/Argument-dependent_name_lookup

    In the C++ programming language, argument-dependent lookup (ADL), or argument-dependent name lookup, [1] applies to the lookup of an unqualified function name depending on the types of the arguments given to the function call. This behavior is also known as Koenig lookup, as it is often attributed to Andrew Koenig, though he is not its inventor ...

  3. Support vector machine - Wikipedia

    en.wikipedia.org/wiki/Support_vector_machine

    A training example of SVM with kernel given by φ((a, b)) = (a, b, a 2 + b 2) Suppose now that we would like to learn a nonlinear classification rule which corresponds to a linear classification rule for the transformed data points ().

  4. Name mangling - Wikipedia

    en.wikipedia.org/wiki/Name_mangling

    The linker needs a great deal of information on each program entity. For example, to correctly link a function it needs its name, the number of arguments and their types, and so on. The simple programming languages of the 1970s, like C, only distinguished subroutines by their name, ignoring other information including parameter and return types.

  5. Polynomial kernel - Wikipedia

    en.wikipedia.org/wiki/Polynomial_kernel

    The hyperplane learned in feature space by an SVM is an ellipse in the input space. In machine learning , the polynomial kernel is a kernel function commonly used with support vector machines (SVMs) and other kernelized models, that represents the similarity of vectors (training samples) in a feature space over polynomials of the original ...

  6. Least-squares support vector machine - Wikipedia

    en.wikipedia.org/wiki/Least-squares_support...

    Least-squares support-vector machines (LS-SVM) for statistics and in statistical modeling, are least-squares versions of support-vector machines (SVM), which are a set of related supervised learning methods that analyze data and recognize patterns, and which are used for classification and regression analysis.

  7. Sequential minimal optimization - Wikipedia

    en.wikipedia.org/wiki/Sequential_minimal...

    Consider a binary classification problem with a dataset (x 1, y 1), ..., (x n, y n), where x i is an input vector and y i ∈ {-1, +1} is a binary label corresponding to it. A soft-margin support vector machine is trained by solving a quadratic programming problem, which is expressed in the dual form as follows:

  8. Variadic macro in the C preprocessor - Wikipedia

    en.wikipedia.org/wiki/Variadic_macro_in_the_C...

    The declaration syntax is similar to that of variadic functions: a sequence of three full stops "..." is used to indicate that one or more arguments must be passed.During macro expansion each occurrence of the special identifier __VA_ARGS__ in the macro replacement list is replaced by the passed arguments.

  9. Most vexing parse - Wikipedia

    en.wikipedia.org/wiki/Most_vexing_parse

    The most vexing parse is a counterintuitive form of syntactic ambiguity resolution in the C++ programming language. In certain situations, the C++ grammar cannot distinguish between the creation of an object parameter and specification of a function's type. In those situations, the compiler is required to interpret the line as a function type ...