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Gradient-based methods such as backpropagation are usually used to estimate the parameters of the network. [4] During the training phase, ANNs learn from labeled training data by iteratively updating their parameters to minimize a defined loss function. [5] This method allows the network to generalize to unseen data.
In measure-theoretic probability theory, the density function is defined as the Radon–Nikodym derivative of the probability distribution relative to a common dominating measure. [5] The likelihood function is this density interpreted as a function of the parameter, rather than the random variable. [ 6 ]
4.2 United States. 4.3 Elsewhere. 5 People. 6 Sport. Toggle Sport subsection. 6.1 Association football (soccer) 6.2 Other sports. 7 Military. 8 Transport. 9 Other ...