Search results
Results from the WOW.Com Content Network
where each network module can be a linear transform, a nonlinear activation function, a convolution, etc. () is the input vector, () is the output vector from the first module, etc. BatchNorm is a module that can be inserted at any point in the feedforward network.
Feature scaling is a method used to normalize the range of independent variables or features of data. In data processing , it is also known as data normalization and is generally performed during the data preprocessing step.
The softmax function, also known as softargmax [1]: 184 or normalized exponential function, [2]: 198 converts a vector of K real numbers into a probability distribution of K possible outcomes. It is a generalization of the logistic function to multiple dimensions, and is used in multinomial logistic regression .
In a neural network, batch normalization is achieved through a normalization step that fixes the means and variances of each layer's inputs. Ideally, the normalization would be conducted over the entire training set, but to use this step jointly with stochastic optimization methods, it is impractical to use the global information.
A whitening transformation or sphering transformation is a linear transformation that transforms a vector of random variables with a known covariance matrix into a set of new variables whose covariance is the identity matrix, meaning that they are uncorrelated and each have variance 1. [1]
In general, the value of the norm is dependent on the spectrum of : For a vector with a Euclidean norm of one, the value of ‖ ‖ is bounded from below and above by the smallest and largest absolute eigenvalues of respectively, where the bounds are achieved if coincides with the corresponding (normalized) eigenvectors.
Every vector in the new set is orthogonal to every other vector in the new set; and the new set and the old set have the same linear span. In addition, if we want the resulting vectors to all be unit vectors, then we normalize each vector and the procedure is called orthonormalization.
In image processing, normalization is a process that changes the range of pixel intensity values. Applications include photographs with poor contrast due to glare, for example.