Alaa Tharwat ToolBox: svmoneclassval(x,xsup,alpha,rho,kernel,kerneloption); - File Exchange

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Highlights from
Alaa Tharwat ToolBox

K=normalizekernel(x,kernel,ke... K=normalizekernel(x,kernel,kerneloption,xsup);
T=phispan(x,phitype,dilation,... USAGE T=phispan(x,phitype,dilation,uo,a,bord1,bord2)
T=waveletspan(x,dilation,uo,a... Usage T=waveletspan(x,dilation,uo,a,leftbound,rightbound)
[DFLD_Trans]=F_JDLDAPro(Train... % Syntax: [DFLD_Trans]=F_JDLDAPro(TrainData,vNumEachClass);
[F,delta]=aci(Y) THESE CODES WERE DEVELOPED WITH MATLAB 3
[K,option]=svmkernel(x,kernel... Usage K=svkernel(x,kernel,kerneloption,xsup,frame,vector,dual);
[P]=GRNN_final(trn,Test,nocla... This function used to design a generalized regression neural network.
[P]=PNN_final(trn,Test,noclas... This function used to design a generalized regression neural network.
[P]=RBE_final(trn,Test,noclas... This function used to claculate exact radial basis network
[P]=RBF_final(trn,Test,noclas... This function used to design radial basis function
[X]=fileaccess(datafile,Indic...
[Xt,Xapp,Alpha,kM,valBeta,wM]... USAGE
[a,b]=sort_knn(ii,y) This function used to sort tow matrices together
[a1]=zigzag(pic1) This code is edited by Tamer Hosney
[c,d]=rncalc(xapp,yapp,kernel... USAGE
[c,d]=rnsolve(K,T,y,lambda)
[eigvect,eigval,Kt]=kernelpca... USAGE
[kernel,KernelInfo]=tensorwav... USAGE
[matdctq]=dct(pic1) This function to calculate the DCT on the picture (pic1)
[p,item,c]=knn(trx,tstx,lblx,... This code use to compute the Knn classification
[phi,psi,xval]=waveletfunctio... Usage
[x,vec]=pca_new_final(data) Remember that each column of the data matrix(input matrix) represent one image or pattern
[xapp,yapp,xtest,ytest,xtest1... Usage
[xsup,alpha,b,pos]=svmclassnp...
[xsup,alpha,multiplier,pos,Ks... USAGE
[xsup,w,b,nbsv,classifier,pos... [xsup,w,b,nbsv,classifier,posSigma]=svmmulticlassoneagainstone(x,y,nbclass,c,epsilon,kernel,kerneloption,verbose);
[xsup,w,b,nbsv,pos,alpha]=svm... USAGE
[xsup,w,b,nbsv,pos,obj]=svmmu... USAGE [xsup,w,b,nbsv,pos,obj]=svmmulticlass(x,y,nbclass,c,epsilon,kernel,kerneloption,verbose);
[xsup,w,b,pos,timeps,alpha,st... % [xsup,w,b,pos,timeps,alpha,status,cost]]=svmclassLS(x,y,c,lambda,kernel,kerneloption,verbose,span,qpsize,chunksize)
[xsup,w,b,pos,timeps,alpha]=s... % [xsup,w,b,pos,timeps,alpha]=svmclassL2LS(x,y,c,lambda,kernel,kerneloption,verbose,span,qpsize,chunksize)
[xsup,w,b,pos]=LPsvmclass(xap... USAGE
[xsup,w,d,pos,timeps,alpha,ob... USAGE [xsup,w,b,pos,timeps,alpha,obj]=svmclass(x,y,c,lambda,kernel,kerneloption,verbose,span, alphainit)
[xsup,w,d,pos,timeps,alpha,ob... USAGE [xsup,w,b,pos,timeps,alpha]=svmclass(x,y,c,lambda,kernel,kerneloption,verbose,span)
[xsup,w,d,rho,pos,timeps,alph... USAGE [xsup,w,b,rho,pos,timeps,alpha]=svmnuclass(x,y,nu,lambda,kernel,kerneloption,verbose,span, alphainit)
[xsup,ysup,w,b,pos]=LPsvmreg(... USAGE
[y,y1,y2]=svmval(x,xsup,w,b,k... USAGE
[ypred,maxi,ypredMat]=svmmult... USAGE ypred=svmmultival(x,xsup,w,b,nbsv,kernel,kerneloption)
[ypred,vote]=svmmultivaloneag... USAGE [ypred,vote]=svmmultivaloneagainstone(x,xsup,w,b,nbsv,kernel,kerneloption,Sigma)
[ypred]=SVM_final(x,Test,y,nb... This code use to compute the SVM classifier
cout(H,x,y,C,ind,c,A,b,lambda)
feature=kernelpcaproj(xpca,xt...
functioneval(x,fonction,a,b)
givrot (x); GIVROT
j=mindist_classifier_type_fin... This function used to calculate the minimum distance between the testing
kernelset(A,kernelsetoption,o... USAGE
monqp(H,c,A,b,C,l,verbose,X,p...
monqp0(H,c,A,b,l,verbose,X,ps...
r2smallestsphere(xapp,kernel,... usage
spanestimate(x,y,kernel,kerne... USAGE
svmoneclassval(x,xsup,alpha,r...
svmreg(x,y,C,epsilon,kernel,k...
svmreg(x,y,C,epsilon,kernel,k...
svmreg(x,y,C,nu,kernel,kernel...
svmregLS(x,y,C,epsilon,kernel...
tst=pcadist_final(tst,vec,m,S... This function used to project the testing image on the features (PCA) space
y=rnval(xapp,xtest,kernel,ker... USAGE
Contents.m
decision_dct_final.m
decision_ica_final.m
decision_lda_final.m
decision_pca_final.m
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from Alaa Tharwat ToolBox by Alaa Tharwat
This toolBox used in the image processing(feature extraction and classification)

svmoneclassval(x,xsup,alpha,rho,kernel,kerneloption);
function ypred= svmoneclassval(x,xsup,alpha,rho,kernel,kerneloption); K=normalizekernel(x,kernel,kerneloption,xsup); ypred=K*alpha+rho;

Highlights from Alaa Tharwat ToolBox

Highlights from
Alaa Tharwat ToolBox