relief {dprep} | R Documentation

## RELIEF Feature Selection

### Description

This function implements the RELIEF feature selection algorithm.

### Usage

    relief(data, nosample, threshold,vnom)

### Arguments

`data` | the dataset for which feature selection will be carried out
`nosample` | number of instances drawn from the original dataset
`threshold` | the cutoff point to select the features
`vnom` | a vector containing the indexes of the nominal features

### Details

The general idea of this method is to choose the features that can be most distinguished between classes. These are known as the relevant features. At each step of an iterative process, an instance x is chosen at random from the dataset and the weight for each feature is updated adcording to the distance of x to its Nearmiss and NearHit.

### Value

`relevant` | a table that gives the frequency with which the feature was selected as relevant over the trials performed, and the average weight of the feature.
`a plot` | a plot of the weights of the features

### Author(s)

Edgar Acuna

### References

KIRA, K. and RENDEL, L. (1992). The Feature Selection Problem : Traditional Methods and a new algorithm. Proc. Tenth National Conference on Artificial Intelligence, MIT Press, 129-134.

KONONENKO, I., SIMEC, E., and ROBNIK-SIKONJA, M. (1997). Overcoming the myopia of induction learning algorithms with RELIEFF. Applied Intelligence Vol7, 1, 39-55.

### Examples

    ##---- Feature Selection ---
    data(my.iris)
    relief(my.iris,150,0.01)

[Package dprep version 1.0 Index]