This function allows to obtain the relevance function values on a set of target variable values given the interpolating points.
The target variable values of the problem.
A named list supplied by the phi.control function with the parameters needed for obtaining the relevance values.
The phi function specifies the regions of interest in the target variable. It does so by performing a Monotone Cubic Spline Interpolation over a set of maximum and minimum relevance points. The notion of relevance can be associated with rarity. Nonetheless, this notion may depend on the domain experts knowledge.
The function returns the relevance values.
Ribeiro, R., 2011. Utility-based regression (Doctoral dissertation, PhD thesis, Dep. Computer Science, Faculty of Sciences - University of Porto).
Fritsch, F.N. and Carlson, R.E., 1980. Monotone piecewise cubic interpolation. SIAM Journal on Numerical Analysis, 17(2), pp.238-246.
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