# Relevance function.

### Description

This function allows to obtain the relevance function values on a set of target variable values given the interpolating points.

### Usage

1 | ```
phi(y, control.parms)
``` |

### Arguments

`y` |
The target variable values of the problem. |

`control.parms` |
A named list supplied by the phi.control function with the parameters needed for obtaining the relevance values. |

### Details

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.

### Value

The function returns the relevance values.

### Author(s)

Rita Ribeiro rpribeiro@dcc.fc.up.pt, Paula Branco paobranco@gmail.com, and Luis Torgo ltorgo@dcc.fc.up.pt

### References

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.

### See Also

`phi.control`

### Examples

1 2 3 4 5 6 7 8 |

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