A computer-implemented method and system for building a neural network is disclosed. The neural network predicts at least one target based upon predictor variables defined in a state space. First, an input data set is retrieved that includes the predictor variables and at least one target associated with the predictor variables for each observation. In the state space, a number of points is inserted in the state space based upon the values of the predictor variables. The number of points is less than the number of observations. A statistical measure is determined that describes a relationship between the observations and the inserted points. Weights and activation functions of the neural network are determined using the statistical measure.

 
Web www.patentalert.com

< Distributed hierarchical evolutionary modeling and visualization of empirical data

< Online learning method in a decision system

> Method for computing all occurrences of a compound event from occurrences of primitive events

> Method for determining the beginning of a second in the signal of a time-signal transmitter

~ 00204