A B C D E F G H I K L M N O P Q R S T V W X Y
| alpha | Class "vm" | 
| alpha-method | Class "gausspr" | 
| alpha-method | Class "kfa" | 
| alpha-method | Class "kqr" | 
| alpha-method | Class "ksvm" | 
| alpha-method | Class "lssvm" | 
| alpha-method | Class "onlearn" | 
| alpha-method | Class "rvm" | 
| alpha-method | Class "vm" | 
| alphaindex | Class "ksvm" | 
| alphaindex-method | Class "gausspr" | 
| alphaindex-method | Class "kfa" | 
| alphaindex-method | Class "kqr" | 
| alphaindex-method | Class "ksvm" | 
| alphaindex-method | Class "lssvm" | 
| anovadot | Kernel Functions | 
| anovakernel-class | Class "kernel" "rbfkernel" "polykernel", "tanhkernel", "vanillakernel" | 
| as.kernelMatrix | Assing kernelMatrix class to matrix objects | 
| as.kernelMatrix-method | Assing kernelMatrix class to matrix objects | 
| as.kernelMatrix-methods | Assing kernelMatrix class to matrix objects | 
| Asymbound | Kernel Maximum Mean Discrepancy. | 
| Asymbound-method | Class "kqr" | 
| AsympH0 | Kernel Maximum Mean Discrepancy. | 
| AsympH0-method | Class "kqr" | 
| b | Class "ksvm" | 
| b-method | Class "kqr" | 
| b-method | Class "ksvm" | 
| b-method | Class "lssvm" | 
| b-method | Class "onlearn" | 
| besseldot | Kernel Functions | 
| besselkernel-class | Class "kernel" "rbfkernel" "polykernel", "tanhkernel", "vanillakernel" | 
| buffer | Class "onlearn" | 
| buffer-method | Class "onlearn" | 
| centers | Class "specc" | 
| centers-method | Class "specc" | 
| coef-method | Gaussian processes for regression and classification | 
| coef-method | Kernel Feature Analysis | 
| coef-method | Kernel Quantile Regression. | 
| coef-method | Class "ksvm" | 
| coef-method | Support Vector Machines | 
| coef-method | Least Squares Support Vector Machine | 
| coef-method | Relevance Vector Machine | 
| convergence | Class "ranking" | 
| convergence-method | Class "ranking" | 
| couple | Probabilities Coupling function | 
| cross | Class "vm" | 
| cross-method | Class "gausspr" | 
| cross-method | Class "kqr" | 
| cross-method | Class "ksvm" | 
| cross-method | Class "lssvm" | 
| cross-method | Class "rvm" | 
| cross-method | Class "vm" | 
| csi | Cholesky decomposition with Side Information | 
| csi-class | Class "csi" | 
| csi-method | Cholesky decomposition with Side Information | 
| csi-methods | Cholesky decomposition with Side Information | 
| diagresidues | Class "inchol" | 
| diagresidues-method | Class "csi" | 
| diagresidues-method | Class "inchol" | 
| dots | Kernel Functions | 
| dual | Class "ipop" | 
| dual-method | Class "ipop" | 
| edgegraph | Class "ranking" | 
| edgegraph-method | Class "ranking" | 
| eig | Class "prc" | 
| eig-method | Class "kha" | 
| eig-method | Class "kpca" | 
| eig-method | Class "prc" | 
| error | Class "vm" | 
| error-method | Class "gausspr" | 
| error-method | Class "kqr" | 
| error-method | Class "ksvm" | 
| error-method | Class "lssvm" | 
| error-method | Class "rvm" | 
| error-method | Class "vm" | 
| eskm-method | Class "kha" | 
| fit-method | Class "onlearn" | 
| fitted-method | Class "ksvm" | 
| fitted-method | Class "vm" | 
| fourierdot | Kernel Functions | 
| fourierkernel-class | Class "kernel" "rbfkernel" "polykernel", "tanhkernel", "vanillakernel" | 
| gausspr | Gaussian processes for regression and classification | 
| gausspr-class | Class "gausspr" | 
| gausspr-method | Gaussian processes for regression and classification | 
| H0 | Kernel Maximum Mean Discrepancy. | 
| H0-method | Class "kqr" | 
| how | Class "ipop" | 
| how-method | Class "ipop" | 
| inchol | Incomplete Cholesky decomposition | 
| inchol-class | Class "inchol" | 
| inchol-method | Incomplete Cholesky decomposition | 
| income | Income Data | 
| inlearn | Onlearn object initialization | 
| inlearn-method | Onlearn object initialization | 
| ipop | Quadratic Programming Solver | 
| ipop-class | Class "ipop" | 
| ipop-method | Quadratic Programming Solver | 
| kcall | Class "vm" | 
| kcall-method | Class "gausspr" | 
| kcall-method | Class "kfa" | 
| kcall-method | Class "kha" | 
| kcall-method | Class "kpca" | 
| kcall-method | Class "kqr" | 
| kcall-method | Class "ksvm" | 
| kcall-method | Class "lssvm" | 
| kcall-method | Class "prc" | 
| kcall-method | Class "rvm" | 
| kcall-method | Class "vm" | 
| kcca | Kernel Canonical Correlation Analysis | 
| kcca-class | Class "kcca" | 
| kcca-method | Kernel Canonical Correlation Analysis | 
| kcor | Class "kcca" | 
| kcor-method | Class "kcca" | 
| kernel-class | Class "kernel" "rbfkernel" "polykernel", "tanhkernel", "vanillakernel" | 
| kernelf | Class "vm" | 
| kernelf-method | Class "gausspr" | 
| kernelf-method | Class "kfa" | 
| kernelf-method | Class "kha" | 
| kernelf-method | Class "kqr" | 
| kernelf-method | Class "kpca" | 
| kernelf-method | Class "kqr" | 
| kernelf-method | Class "ksvm" | 
| kernelf-method | Class "lssvm" | 
| kernelf-method | Class "onlearn" | 
| kernelf-method | Class "prc" | 
| kernelf-method | Class "rvm" | 
| kernelf-method | Class "specc" | 
| kernelf-method | Class "vm" | 
| kernelFast | Kernel Matrix functions | 
| kernelFast-method | Kernel Matrix functions | 
| kernelMatrix | Kernel Matrix functions | 
| kernelMatrix-class | Assing kernelMatrix class to matrix objects | 
| kernelMatrix-method | Kernel Matrix functions | 
| kernelMult | Kernel Matrix functions | 
| kernelMult-method | Kernel Matrix functions | 
| kernelPol | Kernel Matrix functions | 
| kernelPol-method | Kernel Matrix functions | 
| kernels | Kernel Functions | 
| kfa | Kernel Feature Analysis | 
| kfa-class | Class "kfa" | 
| kfa-method | Kernel Feature Analysis | 
| kfunction | Kernel Functions | 
| kfunction-class | Class "kernel" "rbfkernel" "polykernel", "tanhkernel", "vanillakernel" | 
| kha | Kernel Principal Components Analysis | 
| kha-class | Class "kha" | 
| kha-method | Kernel Principal Components Analysis | 
| kkmeans | Kernel k-means | 
| kkmeans-method | Kernel k-means | 
| kmmd | Kernel Maximum Mean Discrepancy. | 
| kmmd-class | Class "kqr" | 
| kmmd-method | Kernel Maximum Mean Discrepancy. | 
| kpar | Kernel Functions | 
| kpar-method | Class "gausspr" | 
| kpar-method | Class "kernel" "rbfkernel" "polykernel", "tanhkernel", "vanillakernel" | 
| kpar-method | Class "kqr" | 
| kpar-method | Class "ksvm" | 
| kpar-method | Class "lssvm" | 
| kpar-method | Class "onlearn" | 
| kpar-method | Class "rvm" | 
| kpar-method | Class "vm" | 
| kpca | Kernel Principal Components Analysis | 
| kpca-class | Class "kpca" | 
| kpca-method | Kernel Principal Components Analysis | 
| kqr | Kernel Quantile Regression. | 
| kqr-class | Class "kqr" | 
| kqr-method | Kernel Quantile Regression. | 
| ksvm | Support Vector Machines | 
| ksvm-class | Class "ksvm" | 
| ksvm-method | Support Vector Machines | 
| laplacedot | Kernel Functions | 
| laplacekernel-class | Class "kernel" "rbfkernel" "polykernel", "tanhkernel", "vanillakernel" | 
| lev | Class "vm" | 
| lev-method | Class "gausspr" | 
| lev-method | Class "ksvm" | 
| lev-method | Class "lssvm" | 
| lev-method | Class "rvm" | 
| lev-method | Class "vm" | 
| lssvm | Least Squares Support Vector Machine | 
| lssvm-class | Class "lssvm" | 
| lssvm-method | Least Squares Support Vector Machine | 
| lssvm-methods | Least Squares Support Vector Machine | 
| maxresiduals | Class "inchol" | 
| maxresiduals-method | Class "csi" | 
| maxresiduals-method | Class "inchol" | 
| mlike | Class "rvm" | 
| mlike-method | Class "rvm" | 
| mmdstats | Kernel Maximum Mean Discrepancy. | 
| mmdstats-method | Class "kqr" | 
| musk | Musk data set | 
| nSV | Class "ksvm" | 
| nSV-method | Class "ksvm" | 
| nSV-method | Class "lssvm" | 
| nvar | Class "rvm" | 
| nvar-method | Class "rvm" | 
| obj | Class "ksvm" | 
| obj-method | Class "ksvm" | 
| onlearn | Kernel Online Learning algorithms | 
| onlearn-class | Class "onlearn" | 
| onlearn-method | Kernel Online Learning algorithms | 
| param | Class "ksvm" | 
| param-method | Class "kqr" | 
| param-method | Class "ksvm" | 
| param-method | Class "lssvm" | 
| pcv | Class "prc" | 
| pcv-method | Class "kha" | 
| pcv-method | Class "kpca" | 
| pcv-method | Class "prc" | 
| pivots | Class "inchol" | 
| pivots-method | Class "csi" | 
| pivots-method | Class "inchol" | 
| plot-method | plot method for support vector object | 
| plot.ksvm | plot method for support vector object | 
| polydot | Kernel Functions | 
| polykernel-class | Class "kernel" "rbfkernel" "polykernel", "tanhkernel", "vanillakernel" | 
| prc-class | Class "prc" | 
| predgain | Class "csi" | 
| predgain-method | Class "csi" | 
| predict-method | Class "kfa" | 
| predict-method | Kernel Principal Components Analysis | 
| predict-method | Kernel Principal Components Analysis | 
| predict-method | Least Squares Support Vector Machine | 
| predict-method | Class "onlearn" | 
| predict-method | predict method for Gaussian Processes object | 
| predict-method | Predict method for kernel Quantile Regression object | 
| predict-method | predict method for support vector object | 
| predict-method | Relevance Vector Machine | 
| predict.gausspr | predict method for Gaussian Processes object | 
| predict.kqr | Predict method for kernel Quantile Regression object | 
| predict.ksvm | predict method for support vector object | 
| primal | Class "ipop" | 
| primal-method | Class "ipop" | 
| prior | Class "ksvm" | 
| prior-method | Class "ksvm" | 
| prob.model | Class "ksvm" | 
| prob.model-method | Class "ksvm" | 
| promotergene | E. coli promoter gene sequences (DNA) | 
| Q | Class "csi" | 
| Q-method | Class "csi" | 
| R | Class "csi" | 
| R-method | Class "csi" | 
| Radbound | Kernel Maximum Mean Discrepancy. | 
| Radbound-method | Class "kqr" | 
| ranking | Ranking | 
| ranking-class | Class "ranking" | 
| ranking-method | Ranking | 
| rbfdot | Kernel Functions | 
| rbfkernel-class | Class "kernel" "rbfkernel" "polykernel", "tanhkernel", "vanillakernel" | 
| reuters | Reuters Text Data | 
| rho | Class "onlearn" | 
| rho-method | Class "onlearn" | 
| rlabels | Reuters Text Data | 
| rotated | Class "kpca" | 
| rotated-method | Class "kpca" | 
| RVindex | Class "rvm" | 
| RVindex-method | Class "rvm" | 
| rvm | Relevance Vector Machine | 
| rvm-class | Class "rvm" | 
| rvm-method | Relevance Vector Machine | 
| rvm-methods | Relevance Vector Machine | 
| scaling | Class "ksvm" | 
| scaling-method | Class "gausspr" | 
| scaling-method | Class "kqr" | 
| scaling-method | Class "ksvm" | 
| scaling-method | Class "lssvm" | 
| show | Class "ksvm" | 
| show-method | Kernel Functions | 
| show-method | Gaussian processes for regression and classification | 
| show-method | Kernel Feature Analysis | 
| show-method | Kernel Maximum Mean Discrepancy. | 
| show-method | Kernel Quantile Regression. | 
| show-method | Support Vector Machines | 
| show-method | Least Squares Support Vector Machine | 
| show-method | Class "onlearn" | 
| show-method | Class "ranking" | 
| show-method | Relevance Vector Machine | 
| show-method | Spectral Clustering | 
| sigest | Hyperparameter estimation for the Gaussian Radial Basis kernel | 
| sigest-method | Hyperparameter estimation for the Gaussian Radial Basis kernel | 
| size | Class "specc" | 
| size-method | Class "specc" | 
| spam | Spam E-mail Database | 
| specc | Spectral Clustering | 
| specc-class | Class "specc" | 
| specc-method | Spectral Clustering | 
| spirals | Spirals Dataset | 
| splinedot | Kernel Functions | 
| splinekernel-class | Class "kernel" "rbfkernel" "polykernel", "tanhkernel", "vanillakernel" | 
| stringdot | String Kernel Functions | 
| stringkernel-class | Class "kernel" "rbfkernel" "polykernel", "tanhkernel", "vanillakernel" | 
| SVindex | Class "ksvm" | 
| SVindex-method | Class "ksvm" | 
| tanhdot | Kernel Functions | 
| tanhkernel-class | Class "kernel" "rbfkernel" "polykernel", "tanhkernel", "vanillakernel" | 
| ticdata | The Insurance Company Data | 
| truegain | Class "csi" | 
| truegain-method | Class "csi" | 
| type | Class "vm" | 
| type-method | Class "gausspr" | 
| type-method | Class "ksvm" | 
| type-method | Class "lssvm" | 
| type-method | Class "onlearn" | 
| type-method | Class "rvm" | 
| type-method | Class "vm" | 
| vanilladot | Kernel Functions | 
| vanillakernel-class | Class "kernel" "rbfkernel" "polykernel", "tanhkernel", "vanillakernel" | 
| vm-class | Class "vm" | 
| withinss | Class "specc" | 
| withinss-method | Class "specc" | 
| xcoef | Class "kcca" | 
| xcoef-method | Class "kcca" | 
| xmatrix | Class "vm" | 
| xmatrix-method | Class "gausspr" | 
| xmatrix-method | Class "kfa" | 
| xmatrix-method | Class "kha" | 
| xmatrix-method | Class "kpca" | 
| xmatrix-method | Class "kqr" | 
| xmatrix-method | Class "ksvm" | 
| xmatrix-method | Class "lssvm" | 
| xmatrix-method | Class "onlearn" | 
| xmatrix-method | Class "prc" | 
| xmatrix-method | Class "rvm" | 
| xmatrix-method | Class "vm" | 
| xvar-method | Class "kcca" | 
| ycoef | Class "kcca" | 
| ycoef-method | Class "kcca" | 
| ymatrix | Class "vm" | 
| ymatrix-method | Class "gausspr" | 
| ymatrix-method | Class "kqr" | 
| ymatrix-method | Class "ksvm" | 
| ymatrix-method | Class "lssvm" | 
| ymatrix-method | Class "rvm" | 
| ymatrix-method | Class "vm" | 
| yvar-method | Class "kcca" |