Add weights-of-evidence functionality for predictive mapping

[chudasama-bijal]

Add weights-of-evidence (wofe) functionality: The WofE is a Bayesian method to estimate the probability of a hypothesis (H) based on the knowledge of occurrence of certain evidential events (E). Applied to predictive mapping of mineral deposits, the hypothesis to be predicted is the probability of existence of the targeted mineral deposit and the evidential events are mapped from the geoscientific datasets representing geological features such as lithology, structures, whole rock geochemistry etc.

Implementation using geospatial datasets involves quantification of spatial associations (i.e., the weights) between mineral deposits and the geospatial evidential layers and subsequent calculations of the posterior probabilities for potential of existence of a mineral deposit.

The WofE functionality will have the following steps:

1. Calculation of weights-of-evidences for multiclass (multi-feature) evidential events,
2. Reclassification of multiclass (multi-feature) evidential events to binary evidential events, based on the weights-of-evidences,
3. Recalculation of generalized weights-of-evidences after reclassification, and
4. Calculating posterior probabilities by combining the generalized weights of all the evidential events.

Computationally, the WofE functionality is to be implemented in the following two parts:

1. Quantifying the spatial association (i.e. weights) between the mineral deposit/occurrence and the evidential events.
2. Updating the posterior probabilities of the deposit occurrence by combining the weights-of-evidences of all the events.