neighbours: Computation of nearest neighbours using a selected distance...

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/Neighbours.R

Description

This function allows to obtain the nearest neighbours of each example in a data set using a distance function selected by the user.

Usage

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neighbours(tgt, dat, dist, p=2, k)

Arguments

tgt

The column of the problem target variable.

dat

A data frame containing the problem data.

dist

A character string specifying the distance function to use in the nearest neighbours evaluation.

p

An optional parameter that is only required if the distance function selected in parameter dist is "p-norm".

k

The number of nearest neighbours to return for each example.

Details

Several distance function are implemented in UBL package. The goal of having such a diversity of distance functions is to provide the users more flexibility regarding the distance used and also to provide distance fucntions that are able to deal with nominal and numeric features. The options available for the distance functions are as follows:

data with only numeric features:

"Manhattan", "Euclidean", "Canberra", "Chebyshev", "p-norm";

data with only nominal features:

"Overlap";

data with both nominal and numeric features:

"HEOM", "HVDM".

When the "p-norm" is selected for the dist parameter, it is also necessary to define the value of parameter p. The value of parameter p sets which "p-norm" will be used. For instance, if p is set to 1, the "1-norm" (or Manhattan distance) is used, and if p is set to 2, the "2-norm" (or Euclidean distance) is applied. For more details regarding the distance functions implemented in UBL package please see the package vignettes.

Value

The function returns a matrix with the indexes of the k nearest neighbours for each example in the data set.

Author(s)

Paula Branco [email protected], Rita Ribeiro [email protected] and Luis Torgo [email protected]

References

Wilson, D.R. and Martinez, T.R. (1997). Improved heterogeneous distance functions. Journal of artificial intelligence research, pp.1-34.

See Also

distances

Examples

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## Not run: 
data(ImbC)
# determine the 2 nearest neighbours of each example in ImbC data set
# using the "HVDM" distance function.
neig1 <- neighbours(3, ImbC, "HVDM", k=2)

# now using the "HEOM" distance function
neig2 <- neighbours(3, ImbC, "HEOM", k=2)

# check the differences
head(neig1)
head(neig2)

## End(Not run)

Example output

Loading required package: MBA
Loading required package: gstat
Loading required package: automap
Loading required package: sp
Loading required package: randomForest
randomForest 4.6-12
Type rfNews() to see new features/changes/bug fixes.
     [,1] [,2]
[1,]  716  670
[2,]  148  473
[3,]  327  774
[4,]  348  351
[5,]  519  593
[6,]  149  498
     [,1] [,2]
[1,]  716  670
[2,]  985  447
[3,]  327  774
[4,]  348  680
[5,]  216  484
[6,]  498  862

UBL documentation built on July 13, 2017, 5:02 p.m.