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contains(string,substring) returns boolean Description Returns whether string contains substring as a substring. This is equivalent to using Find and then detecting that it does not result in the failure condition listed in the third column of the Find section. However, some languages have a simpler way of expressing this test. Related
Most of the functions that operate on C strings are declared in the string.h header (cstring in C++), while functions that operate on C wide strings are declared in the wchar.h header (cwchar in C++). These headers also contain declarations of functions used for handling memory buffers; the name is thus something of a misnomer.
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.
SVM algorithms categorize binary data, with the goal of fitting the training set data in a way that minimizes the average of the hinge-loss function and L2 norm of the learned weights. This strategy avoids overfitting via Tikhonov regularization and in the L2 norm sense and also corresponds to minimizing the bias and variance of our estimator ...
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 ...
Whereas the SVM classifier supports binary classification, multiclass classification and regression, the structured SVM allows training of a classifier for general structured output labels. As an example, a sample instance might be a natural language sentence, and the output label is an annotated parse tree. Training a classifier consists of ...
It is known as the "chunking algorithm". The algorithm starts with a random subset of the data, solves this problem, and iteratively adds examples which violate the optimality conditions. One disadvantage of this algorithm is that it is necessary to solve QP-problems scaling with the number of SVs.
Thus, calling f x, where f:: a-> b-> c, yields a new function f2:: b-> c that can be called f2 b to produce c. The actual type specifications can consist of an actual type, such as Integer, or a general type variable that is used in parametric polymorphic functions, such as a, or b, or anyType. So we can write something like: functionName:: a ...