learn: Learn

In pnn: Probabilistic neural networks

Description

Create or update a Probabilist neural network.

Usage

  learn(set, nn, category.column = 1)

Arguments

set	Data frame representing the training set. The first column is used to define the category of each observation (set category.column if it is not the case).
nn	A Probabilistic neural network with or without training.
category.column	The field number of the category (1 by default).

Details

The function learn aims to create a new Probabilist neural network with a training set, or update the training set of an already trained Probabilist neural network. It sets the parameters model, set, category.column, categories, k and n of the neural network.

Value

A trained Probabilist neural network.

See Also

pnn-package, smooth, perf, guess, norms

Examples

library(pnn)
data(norms)
pnn <- learn(norms)
pnn$model
pnn$set[1:10,]
pnn$category.column
pnn$categories
pnn$k
pnn$n

Example output

Attaching package: 'pnn'

The following object is masked from 'package:stats':

    smooth

[1] "Probabilistic neural network"
   c         x         y
1  A 0.8726356 1.1579697
2  A 1.4049735 1.2477019
3  A 0.5281360 1.0571289
4  A 0.8950413 0.6429697
5  A 1.1552677 1.0348489
6  A 0.9432908 0.7721173
7  A 1.6365944 0.8363744
8  A 1.0147225 0.8764854
9  A 1.2125514 0.8136116
10 A 0.8435029 0.7798957
[1] 1
[1] "A" "B"
[1] 2
[1] 400

pnn documentation built on May 2, 2019, 9:30 a.m.