Skip to contents

Configure rIP smoothing for a search strategy

Source: R/strategy_smoothing.R
smooth_rip.Rd

Helper functions that construct S7 Smoothing objects used by search_strategy() to control how relative identification potential (rIP) is smoothed before scoring.

All helpers are pure configuration; they do not perform any computation by themselves. Backend methods for detect_duplicates() and search_candidates() interpret the resulting Smoothing object.

Usage

smooth_rip_identity()

smooth_rip_log()

smooth_rip_offset(alpha = 0.5)

smooth_rip_softmax(temperature = 1)

Arguments

alpha

Numeric scalar; offset that is added to rIP values prior to normalization. Must be non negative.

temperature

Numeric scalar; softmax temperature parameter. Must be strictly positive.

Value

An object inheriting from Smoothing that can be passed to the smoothing argument of search_strategy().

Details

rIP Smoothing Helpers

Functions

  • smooth_rip_identity(): Identity rIP smoothing (no transformation beyond standard per record normalization). This is the default.

  • smooth_rip_log(): Logarithmic rIP smoothing. Backends typically apply log1p(rIP) and then renormalize within each record and column.

  • smooth_rip_offset(): Offset based rIP smoothing with a constant offset alpha that is added to all rIP values before renormalization.

  • smooth_rip_softmax(): Softmax style rIP smoothing with a temperature parameter that controls how sharp or flat the transformed distribution is.

See also

search_strategy()