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In machine learning, one-class classification (OCC), also known as unary classification or class-modelling, tries to identify objects of a specific class amongst all objects, by primarily learning from a training set containing only the objects of that class, [1] although there exist variants of one-class classifiers where counter-examples are used to further refine the classification boundary.
Each time an object of class X is created, the constructor of counter<X> is called, incrementing both the created and alive count. Each time an object of class X is destroyed, the alive count is decremented. It is important to note that counter<X> and counter<Y> are two separate classes and this is why they will keep separate counts of Xs and Ys.
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Python uses the following syntax to express list comprehensions over finite lists: S = [ 2 * x for x in range ( 100 ) if x ** 2 > 3 ] A generator expression may be used in Python versions >= 2.4 which gives lazy evaluation over its input, and can be used with generators to iterate over 'infinite' input such as the count generator function which ...
In Python, everything is an object, even classes. Classes, as objects, have a class, which is known as their metaclass. Python also supports multiple inheritance and mixins. The language supports extensive introspection of types and classes. Types can be read and compared—types are instances of type. The attributes of an object can be ...
The loop counter is used to decide when the loop should terminate and for the program flow to continue to the next instruction after the loop. A common identifier naming convention is for the loop counter to use the variable names i, j, and k (and so on if needed), where i would be the most outer loop, j the next inner loop, etc. The reverse ...
The initialization of the count array, and the second for loop which performs a prefix sum on the count array, each iterate at most k + 1 times and therefore take O(k) time. The other two for loops, and the initialization of the output array, each take O ( n ) time.
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