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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.
[1] [2] The algorithm assumes that we have no prior knowledge about the accuracy of the algorithms in the pool, but there are sufficient reasons to believe that one or more will perform well. Assume that the problem is a binary decision problem. To construct the compound algorithm, a positive weight is given to each of the algorithms 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.
An index that is weighted in this manner is said to be "float-adjusted" or "float-weighted", in addition to being cap-weighted. For example, the S&P 500 index is both cap-weighted and float-adjusted. [3] Historically, in the United States, capitalization-weighted indices tended to use full weighting, i.e., all outstanding shares were included ...
Theano is an open source project [3] primarily developed by the Montreal Institute for Learning Algorithms (MILA) at the Université de Montréal. [4]The name of the software references the ancient philosopher Theano, long associated with the development of the golden mean.
The NIFTY 50 index is a free float market capitalisation-weighted index. Stocks are added to the index based on the following criteria: [1] Must have traded at an average impact cost of 0.50% or less during the last six months for 90% of the observations, for the basket size of Rs. 100 Million. The company should have a listing history of 6 months.
Set R = {1, ..., n}. Set x to an all-zero vector of dimension n. Set w = A T (y − Ax). Let w R denote the sub-vector with indexes from R; Main loop: while R ≠ ∅ and max(w R) > ε: Let j in R be the index of max(w R) in w. Add j to P. Remove j from R. Let A P be A restricted to the variables included in P. Let s be vector of same length as x.
The difference between the full capitalization, float-adjusted, and equal weight versions is in how the index components are weighted. The full cap index uses the total shares outstanding for each company. The float-adjusted index uses shares adjusted for free float. The equal-weighted index assigns each security in the index the same weight.