R: Evaluate the Discriminatory Power of Individual Bits in a...

bit.importance {fingerprint} | R Documentation

## Evaluate the Discriminatory Power of Individual Bits in a Binary Fingerprint

### Description

This method evaluates the Kullback-Leibler (KL) divergence to rank the individual bits in a binary fingerprint in their ability to discriminate between database and active compounds. This method is implemented based on Nisius and Bajorath and includes an m-estimate correction.

### Usage

    bit.importance(actives, background)

### Arguments

`actives` | A list of fingerprints for the actives
`background` | A list of fingerprints representing the background collection

### Value

A numeric vector of length equal to the size of the fingerprints. Each element of the vector is the KL divergence for the corresponding bit. If a bit position is never set to 1 in any of the compounds from the actives and the background, then the KL divergence for that position is undefined and `NA` is returned.

### Author(s)

Rajarshi Guha rajarshi.guha@gmail.com

### References

Nisius, B.; Bajorath, J.; ChemMedChem, 2010, 5, 859-868.

### See Also

`bit.spectrum`

[Package fingerprint version 3.5.7 Index]