confusion: Classification Confusion Matrix and Accuracy

In rknn: Random KNN Classification and Regression

Description

Compute classification confusion matrix and accuracy

Usage

confusion(obs, pred)
confusion2acc(ct)

Arguments

obs	A vector of observed classes.
pred	A vector of predicted classes.
ct	A table retruned from confusion

Value

confusion return a matrix of cross classification counts. confusion return a overall classification accuracy.

Author(s)

Shengqiao Li<[e-mail]>

Examples

  obs<- rep(0:1, each =5);
  pre<- c(obs[3:10], obs[1:2])
  confusion(obs, pre)
  confusion2acc(  confusion(obs, pre))

Example output

Loading required package: gmp

Attaching package: 'gmp'

The following objects are masked from 'package:base':

    %*%, apply, crossprod, matrix, tcrossprod

               
classified as-> 0 1
              0 3 2
              1 2 3
[1] 0.6

rknn documentation built on May 2, 2019, 12:35 p.m.