function?RESULTS?=?assessment（LabelsPreLabelspar）

%
%???function?RESULTS?=?assessment（LabelsPreLabelspar）
%
%???INPUTS:
%
%???Labels?????????:?A?vector?containing?the?true?（actual）?labels?for?a?given?set?of?sample.
%???PreLabels??????:?A?vector?containing?the?estimated?（predicted）?labels?for?a?given?set?of?sample.
%	par			???:?‘class‘?or?‘regress‘
%
%???OUTPUTS:?（all?contained?in?struct?RESULTS）
%
%???ConfusionMatrix:?Confusion?matrix?of?the?classification?process?（True?labels?in?columns?predictions?in?rows）
%???Kappa??????????:?Estimated?Cohen‘s?Kappa?coefficient
%???OA?????????????:?Overall?Accuracy
%???varKappa???????:?Variance?of?the?estimated?Kappa?coefficient
%???Z??????????????:?A?basic?Z-score?for?significance?testing?（considering?that?Kappa?is?normally?distributed）
%???CI?????????????:?Confidence?interval?at?95%?for?the?estimated?Kappa?coefficient
%???Wilcoxon?sign?test?and?McNemar‘s?test?of?significance?differences
%
%???Gustavo?Camps-Valls?2007（c）
%???gcamps@uv.es
%???
%???Formulae?in:
%???Assessing?the?Accuracy?of?Remotely?Sensed?Data
%???by?Russell?G?Congalton?Kass?Green.?CRC?Press
%

switch?lower（par）
	case?{‘class‘}
	
	Etiquetas?=?union（LabelsPreLabels）;?????%?Class?labels?（usually?123....?but?can?work?with?text?labels）
	NumClases?=?length（Etiquetas）;?%?Number?of?classes
	
	%?Compute?confusion?matrix
????ConfusionMatrix?=?zeros（NumClases）;
	for?i=1:NumClases
	????????for?j=1:NumClases
	????????????????ConfusionMatrix（ij）?=?length（find（PreLabels==Etiquetas（i）?&?Labels==Etiquetas（j）））;
	????????end;
	end;
	??????????
	%?Compute?Overall?Accuracy?and?Cohen‘s?kappa?statistic
	n??????=?sum（ConfusionMatrix（:））;?????????????????????%?Total?number?of?samples
	PA?????=?sum（diag（ConfusionMatrix））;
	OA?????=?PA/n;
	
	%?Estimated?Overall?Cohen‘s?Kappa?（suboptimal?implementation）
	npj?=?sum（ConfusionMatrix1）;
	nip?=?sum（ConfusionMatrix2）;
	PE??=?npj*nip;
????if?（n*PA-PE）?==?0?&&?（n^2-PE）?==?0
????????%?Solve?indetermination
????????warning（‘0?divided?by?0‘）
????????Kappa?=?1;
????else
????	Kappa??=?（n*PA-PE）/（n^2-PE）;
????end
	
	%?Cohen‘s?Kappa?Variance
	theta1?=?OA;
	theta2?=?PE/n^2;
	theta3?=?（nip‘+npj）?*?diag（ConfusionMatrix）??/?n^2;
	
	suma4?=?0;
	for?i=1:NumClases
	for?j=1:NumClases
		suma4?=?suma4?+?ConfusionMatrix（ij）*（nip（i）?+?npj（j））^2;
	end;
	end;
	theta4?=?suma4/n^3;
	varKappa?=?（?theta1*（1-theta1）/（1-theta2）^2?????+?????2*（1-theta1）*（2*theta1*theta2-theta3）/（1-theta2）^3??????+?????（1-theta1）^2*（theta4-4*theta2^2）/（1-theta2）^4??）/n;
	Z?=?Kappa/sqrt（varKappa）;
	CI?=?[Kappa?+?1.96*sqrt（varKappa）?Kappa?-?1.96*sqrt（varKappa）];
	
	if?NumClases==2
	????%?Wilcoxon?test?at?95%?confidence?interval
	????[p1h1]?=?signrank（LabelsPreLabels）;
	????if?h1==0
	????????RESULTS.WilcoxonComment	=?‘The?null?hypothesis?of?both?distributions?come?from?the?same?median?can?be?rejected?at?the?5%?level.‘;
	????elseif?h1==1
	????????RESULTS.WilcoxonComment	=?‘Th

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????目錄???????????0??2016-02-16?07:39??msvr-2-1\
?????文件????????2182??2016-02-16?07:37??msvr-2-1\demoMSVR.m
?????文件????????4689??2010-09-15?09:18??msvr-2-1\assessment.m
?????文件????????1642??2010-09-15?09:18??msvr-2-1\kernelmatrix.m
?????文件????????3312??2016-02-16?07:39??msvr-2-1\msvr.m
?????文件?????????198??2010-09-15?09:18??msvr-2-1\scale.m