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fastmath.kernel.vector

Various vector based kernels

Various vector based kernels
raw docstring

anovaclj

(anova)
(anova {:keys [sigma k d] :or {sigma 1.0 k 1.0 d 1.0}})

Anova kernel.

Parameters:

  • :sigma - multiplier (default: 1.0)
  • :k and :d - exponents (default: 1.0)
Anova kernel.

Parameters:

* `:sigma` - multiplier (default: 1.0)
* `:k` and `:d` - exponents (default: 1.0)
sourceraw docstring

b-splineclj

(b-spline)
(b-spline {:keys [n] :or {n 2.0}})

B-spline kernel with degree :n (default: 2.0).

B-spline kernel with degree `:n` (default: 2.0).
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besselclj

(bessel)
(bessel {:keys [sigma n v distance]
         :or {sigma 1.0 n 2.0 v -1.0 distance v/dist}})

Bessel (of the first kind) kernel

Parameters:

  • :sigma - shape (default: 1.0)
  • :n - exponent factor (default: 2.0)
  • :v - Bessel J order - 1 (default: -1.0)
  • :distance - distance function (default: euclidean)
Bessel (of the first kind) kernel

Parameters:

* `:sigma` - shape (default: 1.0)
* `:n` - exponent factor (default: 2.0)
* `:v` - Bessel J order - 1 (default: -1.0)
* `:distance` - distance function (default: euclidean)
sourceraw docstring

bessel2clj

(bessel2)
(bessel2 {:keys [sigma order degree distance]
          :or {sigma 1.0 order 0.0 degree 1.0 distance v/dist}})

Bessel (of the first kind) kernel, R kernlab implementation.

Parameters:

  • :sigma - shape (default: 1.0)
  • :degree - exponent (default: 1.0)
  • :order - Bessel J order (default: 0.0)
  • :distance - distance function (default: euclidean)
Bessel (of the first kind) kernel, R kernlab implementation.

Parameters:

* `:sigma` - shape (default: 1.0)
* `:degree` - exponent (default: 1.0)
* `:order` - Bessel J order (default: 0.0)
* `:distance` - distance function (default: euclidean)
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cauchyclj

(cauchy)
(cauchy {:keys [sigma distance] :or {sigma 1.0 distance v/dist}})

Cauchy kernel.

Parameters:

  • sigma - scale (default: 1.0)
  • :distance - distance function (default: euclidean)
Cauchy kernel.

Parameters:

* `sigma` - scale (default: 1.0)
* `:distance` - distance function (default: euclidean)
sourceraw docstring

chi-squareclj

(chi-square)
(chi-square _)

Chi-square kernel.

Chi-square kernel.
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chi-square2clj

(chi-square2)
(chi-square2 _)

Chi-square kernel, second version

Chi-square kernel, second version
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dirichletclj

(dirichlet)
(dirichlet {:keys [n] :or {n 1.0}})

Dirichlet kernel with :n dimensionality (default: 1.0).

Dirichlet kernel with `:n` dimensionality (default: 1.0).
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exponentialclj

(exponential)
(exponential {:keys [sigma distance] :or {sigma 1.0 distance v/dist}})

Exponential kernel.

Parameters:

  • :sigma - shape of the kernel (default: 1.0)
  • :distance - distance function (default: euclidean)
Exponential kernel.

Parameters:

* `:sigma` - shape of the kernel (default: 1.0)
* `:distance` - distance function (default: euclidean)
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gaussianclj

(gaussian)
(gaussian {:keys [sigma distance] :or {sigma 1.0 distance v/dist}})

Gaussian kernel.

Parameters:

  • :sigma - shape of the kernel (default: 1.0)
  • :distance - distance function (default: euclidean)
Gaussian kernel.

Parameters:

* `:sigma` - shape of the kernel (default: 1.0)
* `:distance` - distance function (default: euclidean)
sourceraw docstring

generalized-histogramclj

(generalized-histogram)
(generalized-histogram {:keys [p] :or {p 2.0}})

Generalized histogram with :p exponent (default: 2.0).

Generalized histogram with `:p` exponent (default: 2.0).
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generalized-t-studentclj

(generalized-t-student)
(generalized-t-student {:keys [p distance]})

Generalized t-student.

Parameters:

  • :p - exponent
  • :distance - distance function (default: euclidean)
Generalized t-student.

Parameters:

* `:p` - exponent
* `:distance` - distance function (default: euclidean)
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geometricclj

(geometric)
(geometric {:keys [n r distance] :or {r 1.0 distance v/dist}})

Geometric Compactly Supported kernel

Parameters:

  • :n - dimension
  • :r - shape (default: 1.0)
  • :distance - distance function (default: euclidean)

Specific kernel names for :n:

  • 1 - triangular
  • 2 - circular
  • 3 - spherical
Geometric Compactly Supported kernel

Parameters:

* `:n` - dimension
* `:r` - shape (default: 1.0)
* `:distance` - distance function (default: euclidean)

Specific kernel names for `:n`:

* 1 - triangular
* 2 - circular
* 3 - spherical
sourceraw docstring

hellingerclj

(hellinger)
(hellinger _)

Hellinger kernel.

Hellinger kernel.
sourceraw docstring

histogramclj

(histogram)
(histogram _)

Histogram kernel.

Histogram kernel.
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hyperbolic-secantclj

(hyperbolic-secant)
(hyperbolic-secant {:keys [a distance] :or {a 1.0 distance v/dist}})

Hyperbolic secant kernel.

Parameters:

  • :a scaling factor (default: 1.0)
  • :distance - distance function (default: euclidean)
Hyperbolic secant kernel.

Parameters:

* `:a` scaling factor (default: 1.0)
* `:distance` - distance function (default: euclidean)
sourceraw docstring

hyperbolic-tangentclj

(hyperbolic-tangent)
(hyperbolic-tangent {:keys [alpha c] :or {alpha 1.0 c 0.0}})

Hyperbolic tangent of the dot product.

Parameters:

  • :alpha - dot product multiplier (default: 1.0)
  • :c - shift (default: 0.0)
Hyperbolic tangent of the dot product.

Parameters:

* `:alpha` - dot product multiplier (default: 1.0)
* `:c` - shift (default: 0.0)
sourceraw docstring

inverse-multiquadraticclj

(inverse-multiquadratic)
(inverse-multiquadratic {:keys [c distance] :or {c 1.0 distance v/dist}})

Inverse multiquadratic kernel.

Parameters:

:c - shift (default: 1.0) :distance - distance function (default: euclidean)

Inverse multiquadratic kernel.

Parameters:

`:c` - shift (default: 1.0)
`:distance` - distance function (default: euclidean)
sourceraw docstring

laplacianclj

(laplacian)
(laplacian {:keys [sigma distance] :or {sigma 1.0 distance v/dist}})

Laplacian kernel.

Parameters:

  • :sigma - shape of the kernel (default: 1.0)
  • :distance - distance function (default: euclidean)
Laplacian kernel.

Parameters:

* `:sigma` - shape of the kernel (default: 1.0)
* `:distance` - distance function (default: euclidean)
sourceraw docstring

linearclj

(linear)
(linear _)

Dot product kernel

Dot product kernel
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logclj

(log)
(log {:keys [p distance]})

Logarithmic.

Parameters:

  • :p - exponent (default: 2.0)
  • :distance - distance function (default: euclidean)
Logarithmic.

Parameters:

* `:p` - exponent (default: 2.0)
* `:distance` - distance function (default: euclidean)
sourceraw docstring

maternclj

(matern)
(matern {:keys [order theta distance] :or {order 1 theta 1.0 distance v/dist}})

Matern kernel.

Parameters:

  • :order - order of the kernel, should be odd (default: 1).
  • :theta - shape (default: 1.0)
  • :distance - distance function (default: euclidean)

Order of the Bessel K function is a half of :order parameter. For example to get Matern 5/2 kernel, call (matern 5).

Matern kernel.

Parameters:

* `:order` - order of the kernel, should be odd (default: 1).
* `:theta` - shape (default: 1.0)
* `:distance` - distance function (default: euclidean)

Order of the Bessel K function is a half of `:order` parameter. For example to get Matern 5/2 kernel, call `(matern 5)`.
sourceraw docstring

multiquadraticclj

(multiquadratic)
(multiquadratic {:keys [c distance] :or {c 1.0 distance v/dist}})

Multiquadratic kernel.

Parameters:

:c - shift (default: 1.0) :distance - distance function (default: euclidean)

Multiquadratic kernel.

Parameters:

`:c` - shift (default: 1.0)
`:distance` - distance function (default: euclidean)
sourceraw docstring

pearsonclj

(pearson)
(pearson {:keys [sigma omega distance]
          :or {sigma 1.0 omega 1.0 distance v/dist}})

Pearson VII kernel

Parameters:

  • :sigma - scale (default: 1.0)
  • :omega - exponent (default: 1.0)
  • :distance - distance function (default: euclidean)
Pearson VII kernel

Parameters:

* `:sigma` - scale (default: 1.0)
* `:omega` - exponent (default: 1.0)
* `:distance` - distance function (default: euclidean)
sourceraw docstring

periodicclj

(periodic)
(periodic {:keys [sigma periodicity distance]
           :or {sigma 1.0 periodicity 1.0 distance v/dist}})

Periodic kernel.

Parameters:

  • :sigma - scale (default: 1.0)
  • :periodicity - periodicity (default: 1.0)
  • :distance - distance function (default: euclidean)
Periodic kernel.

Parameters:

* `:sigma` - scale (default: 1.0)
* `:periodicity` - periodicity (default: 1.0)
* `:distance` - distance function (default: euclidean)
sourceraw docstring

polynomialclj

(polynomial)
(polynomial {:keys [alpha c p] :or {alpha 1.0 c 0.0 p 2.0}})

Polynomial (power of dot product).

Parameters:

  • :alpha - dot product multiplier (default: 1.0)
  • :c - shift (default: 0.0)
  • :p - exponent (default: 2.0)
Polynomial (power of dot product).

Parameters:

* `:alpha` - dot product multiplier (default: 1.0)
* `:c` - shift (default: 0.0)
* `:p` - exponent (default: 2.0)
sourceraw docstring

powerclj

(power)
(power {:keys [p distance] :or {p 2.0 distance v/dist}})

Power (negative) of distance.

Parameters:

  • :p - exponent (default: 2.0)
  • :distance - distance function (default: euclidean)
Power (negative) of distance.

Parameters:

* `:p` - exponent (default: 2.0)
* `:distance` - distance function (default: euclidean)
sourceraw docstring

rational-quadraticclj

(rational-quadratic)
(rational-quadratic {:keys [c distance] :or {c 1.0 distance v/dist}})

Rational quadratic kernel.

Parameters:

:c - shift (default: 1.0) :distance - distance function (default: euclidean)

Rational quadratic kernel.

Parameters:

`:c` - shift (default: 1.0)
`:distance` - distance function (default: euclidean)
sourceraw docstring

rbf->kernelclj

(rbf->kernel rbf-kernel)
(rbf->kernel rbf-kernel distance)

Convert RBF kernel as vector kernel using a distance function (default: euclidean).

Convert RBF kernel as vector kernel using a `distance` function (default: euclidean).
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splineclj

(spline)
(spline _)

Spline kernel.

Spline kernel.
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waveclj

(wave)
(wave {:keys [sigma distance] :or {sigma 1.0 distance v/dist}})

Wave (sinc) kernel.

Parameters:

  • :sigma - scale (default: 1.0)
  • :distance - distance function (default: euclidean)
Wave (sinc) kernel.

Parameters:

* `:sigma` - scale (default: 1.0)
* `:distance` - distance function (default: euclidean)
sourceraw docstring

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