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In machine learning, Platt scaling or Platt calibration is a way of transforming the outputs of a classification model into a probability distribution over classes.The method was invented by John Platt in the context of support vector machines, [1] replacing an earlier method by Vapnik, but can be applied to other classification models. [2]
Examples of algorithms for this task include New Edge-Directed Interpolation (NEDI), [1] [2] Edge-Guided Image Interpolation (EGGI), [3] Iterative Curvature-Based Interpolation (ICBI), [citation needed] and Directional Cubic Convolution Interpolation (DCCI). [4] A study found that DCCI had the best scores in PSNR and SSIM on a series of test ...
[3] [4] The shift-and-add method (more recently "image-stacking" method) is a form of speckle imaging commonly used for obtaining high quality images from a number of short exposures with varying image shifts. [5] [6] It has been used in astronomy for several decades, and is the basis for the image stabilisation feature on some cameras. The ...
For the stack, priority queue, deque, and DEPQ types, peek can be implemented in terms of pop and push (if done at same end). For stacks and deques this is generally efficient, as these operations are O (1) in most implementations, and do not require memory allocation (as they decrease the size of the data) – the two ends of a deque each ...
[2] [3] Subroutines and a two-level stack had already been implemented in Konrad Zuse's Z4 in 1945. [4] [5] Klaus Samelson and Friedrich L. Bauer of Technical University Munich proposed the idea of a stack called Operationskeller ("operational cellar") in 1955 [6] [7] and filed a patent in 1957.
In queueing theory, a discipline within the mathematical theory of probability, a Markovian arrival process (MAP or MArP [1]) is a mathematical model for the time between job arrivals to a system. The simplest such process is a Poisson process where the time between each arrival is exponentially distributed. [2] [3]
A scalar processor is classified as a single instruction, single data processor in Flynn's taxonomy.The Intel 486 is an example of a scalar processor. It is to be contrasted with a vector processor where a single instruction operates simultaneously on multiple data items (and thus is referred to as a single instruction, multiple data processor). [2]
*/ /* This implementation does not implement composite functions, functions with a variable number of arguments, or unary operators. */ while there are tokens to be read: read a token if the token is: - a number: put it into the output queue - a function: push it onto the operator stack - an operator o 1: while ( there is an operator o 2 at the ...