perf: Perf

In pnn: Probabilistic neural networks

Description

Performance of a Probabilist neural network.

Usage

  perf(nn)

Arguments

nn	A trained and smoothed Probabilist neural network.

Details

The function perf uses a hold-out method. This method takes the training set used by the function learn and iterate over each observation trying to guess the current observation with a reduced training set (without the current observation).It generates:

• Two lists of observed and guessed values.

• the following statistics: number of success and fails, a sucess rate (success_rate) and a bic indicator.

Value

A probabilist neural network updated with its performance.

See Also

pnn-package, learn, smooth, guess, norms

Examples

library(pnn)
data(norms)
pnn <- learn(norms)
pnn <- smooth(pnn, sigma=0.8)
pnn <- perf(pnn)
pnn$observed
pnn$guessed
pnn$success
pnn$fails
pnn$success_rate
pnn$bic

Example output

Attaching package: 'pnn'

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

    smooth

  [1] A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A
 [38] A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A
 [75] A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A
[112] A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A
[149] A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A
[186] A A A A A A A A A A A A A A A B B B B B B B B B B B B B B B B B B B B B B
[223] B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B
[260] B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B
[297] B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B
[334] B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B
[371] B B B B B B B B B B B B B B B B B B B B B B B B B B B B B B
Levels: A B
  [1] A A A A A A B A A A A A A A A A A A A A A A A A A A A A A A A A A A B A A
 [38] A A A A A A A A A A A A A A A A A A A A A A B A A A A A A A B A A A B A B
 [75] A A B A A A A A B A A A A A A A A A A A A A A A A A A A A A A A A A A A A
[112] A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A
[149] A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A
[186] A A A A A A A A A A A A A A A B B B B B A B B A B B B B B B B B B B B B B
[223] B B B B A B B B B B B B B B B B B B A A B B B B B B B B B B B B B A B B B
[260] B B B B B B A B B A A B B B B B B B B B B B B B A A B B B B B B B B B B B
[297] B B B B A B A B B B B B B B B B B B B B B B B B B B B B B B B A B B B B B
[334] B B B B B B B B A B B A B B B B B B B A B B B B B B B B B B B B A B B A B
[371] B B B B B B B B B B B B B B B B B B A B B B B A B B B B B B
Levels: A B
[1] 371
[1] 29
[1] 0.9275
[1] -1036.683

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