Automatic segmentation of data derived from learned features of a predictive statistical model
Abstract:
A mechanism is provided in a data processing system comprising a processor and a memory, the memory comprising instructions executed by the processor to specifically configure the processor to implement a statistical model tool for providing insight into decision making. The statistical model tool applies the statistical model to an input image to generate an original classification probability. An image modification component executing within the statistical model tool iterative modifies each portion of the input image to generate a modified image. The statistical model tool applies the statistical model to the modified image to generate a new classification probability for each portion of the input image. A compare component executing in the statistical model tool compares each new classification probability to the original classification probability to generate a respective probability distance. A distance map generator executing within the statistical model tool generates a distance map data structure based on the probability distances. The distance map data structure represents an impact each portion of the input image has on determining classification probability by the statistical model.
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