Patent ID: 6941287

Claim:
A computer-implemented method of selecting a feature set having a global informational content above a predefined threshold, the feature set being selected from an initial feature set of inputs corresponding to inputs to a system having measurable inputs and outputs, wherein a large number of input data points to the system and corresponding output data points from the system are acquired to define a data set, and the acquired input and output data points are stored in a storage device, the method comprising the steps of: (a) creating a plurality of feature subspaces, each said feature subspace comprising a set of features from the data set, (b) quantizing the inputs of the data set, the inputs having a range of values, by dividing the range of values into subranges, thereby dividing said feature subspace into a plurality of cells, (c) determining the global level of informational content of each feature subspace by calculating at least one local cell Nishi-formulated entropy E to define a local entropic weight W as the complement of the Nishi-formulated entropy E (W=1−E), and (d) selecting at least one feature set that has a global informational content above the predefined threshold.