TITLE:: FluidKNN
summary:: K Nearest Neighbours machine learning
categories:: FluidManipulation
related:: Classes/FluidKDTree

DESCRIPTION::
Simple machine learning tasks (classification and regression) using K Nearest Neighbours.

See
https://scikit-learn.org/stable/modules/neighbors.html#nearest-neighbors-classification

https://scikit-learn.org/stable/modules/neighbors.html#nearest-neighbors-regression


CLASSMETHODS::

INSTANCEMETHODS::

METHOD:: fit
'Train' the KNN on a source link::Classes/FluidDataSet::

ARGUMENT:: dataset
source link::Classes/FluidDataSet::

ARGUMENT:: action
A function to run when fitting is complete

METHOD:: regress
Map a point between a source link::Classes/FluidDataSet:: used when link::Classes/FluidKNN#index::ing this KNN, and a target data set passed as an argument.

For this to work, the target data set must have labels in common with the source data set. The code::k:: nearest neighbours to the supplied data point are retrrived from the source tree, and then a mapping is obtained through the average of the equivalently labelled points in the target data set.

WARNING:: For now the target data set can only be 1D::

ARGUMENT:: buffer
The data point to map, in a link::Classes/Buffer::

ARGUMENT:: dataset
The target link::Classes/FluidDataSet::

ARGUMENT:: k
The number of neighbours to use in the estimation

ARGUMENT:: action
A function to run when the server responds, taking the value of the regressed point as its argument

METHOD:: classify
Classify a point, using categories from the supplied label set, which maps labels from the source data set to category IDs. This works by getting the labels of the code::k:: nearest points to the passed data point from the source data set, and looking up their IDs in the passed label set. The most frequently ocurring ID is designated as the class for the point.

ARGUMENT:: buffer
The data point to classify, in a link::Classes/Buffer::

ARGUMENT:: labelset
A link::Classes/FluidLabelSet:: of categories mapped to labels in source data set

ARGUMENT:: k
The number of neighbours to use in the classificaton

ARGUMENT:: action
A function to run when the server responds, taking the assigned label as its argument



EXAMPLES::

code::
(some example code)
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