bases {qkerntool} | R Documentation |
The kernel generating functions provided in qkerntool.
The Non Linear Kernel k(x,y) = \frac{1}{2(1-q)}(q^{-\alpha||x||^2}+q^{-\alpha||y||^2}-2q^{-\alpha x'y})
.
The Gaussian kernel k(x,y) =\frac{1}{1-q} (1-q^{(||x-y||^2/\sigma)})
.
The Laplacian Kernel k(x,y) =\frac{1}{1-q} (1-q^{(||x-y||/\sigma)})
.
The Rational Quadratic Kernel k(x,y) =\frac{1}{1-q} (1-q^{\frac{||x-y||^2}{||x-y||^2+c}})
.
The Multiquadric Kernel k(x,y) =\frac{1}{1-q} (q^c-q^{\sqrt{||x-y||^2+c}})
.
The Inverse Multiquadric Kernel k(x,y) =\frac{1}{1-q} (q^{-\frac{1}{c}}-q^{-\frac{1}{\sqrt{||x-y||^2+c}}})
.
The Wave Kernel k(x,y) =\frac{1}{1-q} (q^{-1}-q^{-\frac{\theta}{||x-y||}\sin{\frac{||x-y||}{\theta}}})
.
The d Kernel k(x,y) = \frac{1}{1-q}[1-q^(||x-y||^d)]
.
The Log Kernel k(x,y) =\frac{1}{1-q} [1-q^ln(||x-y||^d+1)]
.
The Cauchy Kernel k(x,y) =\frac{1}{1-q} (q^{-1}-q^{-\frac{1}{1+||x-y||^2/\sigma}})
.
The Chi-Square Kernel k(x,y) =\frac{1}{1-q} (1-q^{\sum{2(x-y)^2/(x+y)} \gamma})
.
The Generalized T-Student Kernel k(x,y) =\frac{1}{1-q} (q^{-1}-q^{-\frac{1}{1+||x-y||^d}})
.
rbfbase(sigma=1,q=0.8)
nonlbase(alpha = 1,q = 0.8)
laplbase(sigma = 1, q = 0.8)
ratibase(c = 1, q = 0.8)
multbase(c = 1, q = 0.8)
invbase(c = 1, q = 0.8)
wavbase(theta = 1,q = 0.8)
powbase(d = 2, q = 0.8)
logbase(d = 2, q = 0.8)
caubase(sigma = 1, q = 0.8)
chibase(gamma = 1, q = 0.8)
studbase(d = 2, q = 0.8)
q |
for all the qkernel function. |
sigma |
for the Radial Basis qkernel function "rbfbase" , the Laplacian qkernel function "laplbase" and the Cauchy qkernel function "caubase". |
alpha |
for the Non Linear qkernel function "nonlbase". |
c |
for the Rational Quadratic qkernel function "ratibase" , the Multiquadric qkernel function "multbase" and the Inverse Multiquadric qkernel function "invbase". |
theta |
for the Wave qkernel function "wavbase". |
d |
for the d qkernel function "powbase" , the Log qkernel function "logbase" and the Generalized T-Student qkernel function "studbase". |
gamma |
for the Chi-Square qkernel function "chibase". |
The kernel generating functions are used to initialize a kernel
function
which calculates the kernel function value between two feature vectors in a
Hilbert Space. These functions can be passed as a qkernel
argument on almost all
functions in qkerntool(e.g., qkgda
, qkpca
etc).
Return an S4 object of class qkernel
which extents the
function
class. The resulting function implements the given
kernel calculating the kernel function value between two vectors.
qpar |
a list containing the kernel parameters (hyperparameters) used. |
The kernel parameters can be accessed by the qpar
function.
Yusen Zhang
yusenzhang@126.com
qkfunc <- rbfbase(sigma=1,q=0.8)
qkfunc
qpar(qkfunc)
## create two vectors
x <- rnorm(10)
y <- rnorm(10)
## calculate dot product
qkfunc(x,y)