Virtual Computational Chemistry Laboratory

Input data Output results Example List of key words


Keyword of Binary Type

This keyword indicates which method will be used to optimise input variables. This option is useful if you want to eliminate redundant variables. The opruning procedures are described in references Tetko et al., 1997 and Kovalishyn, et. al. 1998. In general, sensetivities (or redundances) of input variables are estimated following ensemble calculations and the least sensetive (or most redundant) variable is eliminated. The pruning determines set of input variables that calculates the smallest error for the validation data set. This parameter should be used if pruning option is selected in ANALYSIS.

The available pruning options include next sensetivity calculation methods:

wikel {1} Sensetivity is estimated as a sum of absolute values of outgoing weights.
tetko {2} Similar to previous approach but using normalized weights.
obd {4} Sensetivy is estimated according to the second derivatives of the network error as a function of weights. The higher order and off-diagonal elements of the Hessian matrix are ignored.

More details about the implementation of pruning methods and their comparison can be found in Tetko et al, 1996, Kovalishyn et al, 1998.

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