finco {dprep} | R Documentation

## FINCO Feature Selection Algorithm

### Description

This function selects features using the FINCO algorithm. The dataset must contain only discretized values.

### Usage

    finco(data, level)

### Arguments

`data` | name of the dataset containing the discretized values
`level` | minimum inconsistency level

### Details

The level value must be greater than the inconsistency of the whole dataset, which first must be discretized. The function inconsist included in this library computes inconsistencies. A small value of level yields a greater number of selected features.

### Value

`varselec` | index of selected features
`inconsis` | inconsistency rates of the selected features

### Author(s)

Edgar Acuna

### References

Acuna, E , (2003) A comparison of filters and wrappers for feature selection in supervised classification. Proceedings of the Interface 2003 Computing Science and Statistics. Vol 34.

Acuna, E., Coaquira, F. and Gonzalez, M. (2003). A comparison of feature selection procedures for classifiers based on kernel density estimation. Proc. of the Int. Conf. on Computer, Communication and Control technologies, CCCT03. VolI. p. 468-472. Orlando, Florida.

### See Also

`inconsist`,`lvf`

### Examples

    #---- Feature Selection with FINCO
    data(my.iris)
    disciris=disc.ew(my.iris,1:6)
    inconsist(disciris)
    finco(disciris,0.05)

[Package dprep version 1.0 Index]