Confusion Matrix

Simple multiclass confusion matrix generator with statistics for classifier evaluation.

Statistical measures available (per class and overall):

1. Accuracy
2. Precision
3. Recall
4. Specificity

Usage:

predicted_vals = [ 0 0 0 1 1 1 2 2 2 ];
actual_vals =    [ 0 0 1 1 1 1 1 2 2 ];
[ conf acc prec rec spec ] = confusionMatrix(predicted_vals, actual_vals);

Output:

Confusion matrix
================

Actual values →		0		1		2
Predictions ↓
	0		2		1		0
	1		0		3		0
	2		0		1		2

Statistical measures per class
==============================

		Accuracy	Precision	Recall		Specificity
Class 0		0.888889	0.666667	1.000000	0.857143

Class 1		0.777778	1.000000	0.600000	1.000000

Class 2		0.888889	0.666667	1.000000	0.857143

Averages of measures
====================

Accuracy: 	0.851852
Precision: 	0.777778
Recall: 	0.866667
Specificity: 	0.904762

Confusion matrix and average measures returned:

> conf
conf =

   2           1           0
   0           3           0
   0           1           2

> acc
acc =    0.85185
> prec
prec =    0.77778
> rec
rec =    0.86667
> spec
spec =    0.90476