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A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
In Fixed Channel Allocation or Fixed Channel Assignment (FCA) each cell is given a predetermined set of frequency channels. FCA requires manual frequency planning, which is an arduous task in time-division multiple access (TDMA) and frequency-division multiple access (FDMA) based systems since such systems are highly sensitive to co-channel interference from nearby cells that are reusing the ...
Dynamic Frequency Selection (DFS) is a channel allocation scheme specified for wireless LANs, commonly known as Wi-Fi. It is designed to prevent electromagnetic interference by avoiding co-channel operation with systems that predated Wi-Fi, such as military radar , satellite communication , and weather radar , and also to provide on aggregate a ...
The plain transformer architecture had difficulty converging. In the original paper [1] the authors recommended using learning rate warmup. That is, the learning rate should linearly scale up from 0 to maximal value for the first part of the training (usually recommended to be 2% of the total number of training steps), before decaying again.
Pachinko allocation was first described by Wei Li and Andrew McCallum in 2006. [3] The idea was extended with hierarchical Pachinko allocation by Li, McCallum, and David Mimno in 2007. [4] In 2007, McCallum and his colleagues proposed a nonparametric Bayesian prior for PAM based on a variant of the hierarchical Dirichlet process (HDP). [2]
Direct coupling analysis or DCA is an umbrella term comprising several methods for analyzing sequence data in computational biology. [1] The common idea of these methods is to use statistical modeling to quantify the strength of the direct relationship between two positions of a biological sequence , excluding effects from other positions.
In the theory of computation, a branch of theoretical computer science, a deterministic finite automaton (DFA)—also known as deterministic finite acceptor (DFA), deterministic finite-state machine (DFSM), or deterministic finite-state automaton (DFSA)—is a finite-state machine that accepts or rejects a given string of symbols, by running ...
Depth-first search (DFS) is an algorithm for traversing or searching tree or graph data structures. The algorithm starts at the root node (selecting some arbitrary node as the root node in the case of a graph) and explores as far as possible along each branch before backtracking.