knn: K-Nearest-Neighbors.

In phil8192/lazy-iris: Lazy Learning on the Iris Dataset

Description

Implementation of the k-NN method.

Usage

knn(query, feature.space, k = 1, d.fun = euclidean)

Arguments

query	A list of labeled parameters to query for.
feature.space	The feature space to query against.
k	The k nearest neighbours to return. Default: 1.
d.fun	The distance function to use. Default: euclidean.

Value

The top k nearest neighours in the feature space with respect to the query.

Author(s)

phil

Examples

# form the query instance.
query <- list(
    sepal.length=5.84,
    sepal.width=3.05,
    petal.length=3.76,
    petal.width=1.20)

# obtain the nearest-neighbour
top.1 <- knn(query, iris.data, 1)
print(top.1, row.names=FALSE)

phil8192/lazy-iris documentation built on May 25, 2019, 2:56 a.m.