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There are many variations of the weighted majority algorithm to handle different situations, like shifting targets, infinite pools, or randomized predictions. The core mechanism remains similar, with the final performances of the compound algorithm bounded by a function of the performance of the specialist (best performing algorithm) in the pool.
This algorithm can easily be adapted to compute the variance of a finite population: simply divide by n instead of n − 1 on the last line.. Because SumSq and (Sum×Sum)/n can be very similar numbers, cancellation can lead to the precision of the result to be much less than the inherent precision of the floating-point arithmetic used to perform the computation.
Rendezvous or highest random weight (HRW) hashing [1] [2] is an algorithm that allows clients to achieve distributed agreement on a set of options out of a possible set of options. A typical application is when clients need to agree on which sites (or proxies) objects are assigned to.
Hasse diagram of some classes of quantitative automata, ordered by expressiveness. [1]: Fig.1 In theoretical computer science and formal language theory, a weighted automaton or weighted finite-state machine is a generalization of a finite-state machine in which the edges have weights, for example real numbers or integers.
Following the weight update rule in weighted majority algorithm, the predictions made by the algorithm would be randomized. The algorithm calculates the probabilities of experts predicting positive or negatives, and then makes a random decision based on the computed fraction: [ further explanation needed ]
Calculus on finite weighted graphs is used in a wide range of applications from different fields such as image processing, machine learning, and network analysis. A non-exhaustive list of tasks in which finite weighted graphs have been employed is: image denoising [2] [3] image segmentation [4] image inpainting [2] [5] tomographic ...
That way, using the example of an S&P 500 index fund, each company would be .2% of the fund. ... Gotham launched its first value-weighted index fund, the Formula Investing U.S. Value 100 , in ...
One very early weighted estimator is the Horvitz–Thompson estimator of the mean. [3] When the sampling probability is known, from which the sampling population is drawn from the target population, then the inverse of this probability is used to weight the observations. This approach has been generalized to many aspects of statistics under ...