Started to fix some wrong ref missing refs

Author: theogf

docs/src/api.md

@@ -24,13 +24,21 @@ ExponentiatedKernel
 MaternKernel
 Matern32Kernel
 Matern52Kernel
+NeuralNetworkKernel
+GaborKernel
+EyeKernel
+FBMKernel
+CosineKernel
 LinearKernel
 PolynomialKernel
+PiecewisePolynomialKernel
+MahalanobisKernel
 RationalQuadraticKernel
 GammaRationalQuadraticKernel
 PeriodicKernel
 ZeroKernel
 ConstantKernel
+WienerKernel
 WhiteKernel
 ```
 
@@ -49,8 +57,10 @@ KernelProduct
 Transform
 IdentityTransform
 ScaleTransform
-LowRankTransform
+ARDTransform
+LinearTransform
 FunctionTransform
+SelectTransform
 ChainTransform
 ```
 
@@ -63,9 +73,16 @@ kerneldiagmatrix
 kerneldiagmatrix!
 kernelpdmat
 kernelkronmat
+nystrom
 transform
 ```
 
+## Utilities
+
+```@docs
+ColVecs
+RowVecs
+```
 
 ## Index
 

docs/src/kernels.md

@@ -10,153 +10,172 @@ These are the basic kernels without any transformation of the data. They are the
 
 ### Exponential Kernel
 
-The [Exponential Kernel](@ref ExponentialKernel) is defined as
+The [`ExponentialKernel`](@ref) is defined as
 ```math
-  k(x,x') = \exp\left(-|x-x'|\right)
+  k(x,x') = \exp\left(-|x-x'|\right).
 ```
 
 ### Square Exponential Kernel
 
-The [Square Exponential Kernel](@ref KernelFunctions.SqExponentialKernel) is defined as
+The [`SqExponentialKernel`](@ref) is defined as
 ```math
-  k(x,x') = \exp\left(-\|x-x'\|^2\right)
+  k(x,x') = \exp\left(-\|x-x'\|^2\right).
 ```
 
 ### Gamma Exponential Kernel
 
-The [Gamma Exponential Kernel](@ref KernelFunctions.GammaExponentialKernel) is defined as
+The [`GammaExponentialKernel`](@ref) is defined as
 ```math
-  k(x,x';\gamma) = \exp\left(-\|x-x'\|^{2\gamma}\right)
+  k(x,x';\gamma) = \exp\left(-\|x-x'\|^{2\gamma}\right),
 ```
+where $\gamma > 0$.
 
 ## Matern Kernels
 
 ### Matern Kernel
 
-The [Matern Kernel](@ref KernelFunctions.MaternKernel) is defined as
+The [`MaternKernel`](@ref) is defined as
 
 ```math
-  k(x,x';\nu) = \frac{2^{1-\nu}}{\Gamma(\nu)}\left(\sqrt{2\nu}|x-x'|\right)K_\nu\left(\sqrt{2\nu}|x-x'|\right)
+  k(x,x';\nu) = \frac{2^{1-\nu}}{\Gamma(\nu)}\left(\sqrt{2\nu}|x-x'|\right)K_\nu\left(\sqrt{2\nu}|x-x'|\right),
 ```
 
+where $\nu > 0$.
+
 ### Matern 3/2 Kernel
 
-The [Matern 3/2 Kernel](@ref KernelFunctions.Matern32Kernel) is defined as
+The [`Matern32Kernel`](@ref) is defined as
 
 ```math
-  k(x,x') = \left(1+\sqrt{3}|x-x'|\right)\exp\left(\sqrt{3}|x-x'|\right)
+  k(x,x') = \left(1+\sqrt{3}|x-x'|\right)\exp\left(\sqrt{3}|x-x'|\right).
 ```
 
 ### Matern 5/2 Kernel
 
-The [Matern 5/2 Kernel](@ref KernelFunctions.Matern52Kernel) is defined as
+The [`Matern52Kernel`](@ref) is defined as
 
 ```math
-  k(x,x') = \left(1+\sqrt{5}|x-x'|+\frac{5}{2}\|x-x'\|^2\right)\exp\left(\sqrt{5}|x-x'|\right)
+  k(x,x') = \left(1+\sqrt{5}|x-x'|+\frac{5}{2}\|x-x'\|^2\right)\exp\left(\sqrt{5}|x-x'|\right).
 ```
 
 ## Rational Quadratic
 
 ### Rational Quadratic Kernel
 
-The [Rational Quadratic Kernel](@ref KernelFunctions.RationalQuadraticKernel) is defined as
+The [`RationalQuadraticKernel`](@ref) is defined as
 
 ```math
-  k(x,x';\alpha) = \left(1+\frac{\|x-x'\|^2}{\alpha}\right)^{-\alpha}
+  k(x,x';\alpha) = \left(1+\frac{\|x-x'\|^2}{\alpha}\right)^{-\alpha},
 ```
 
+where $\alpha > 0$.
+
 ### Gamma Rational Quadratic Kernel
 
-The [Gamma Rational Quadratic Kernel](@ref KernelFunctions.GammaRationalQuadraticKernel) is defined as
+The [`GammaRationalQuadraticKernel`](@ref) is defined as
 
 ```math
-  k(x,x';\alpha,\gamma) = \left(1+\frac{\|x-x'\|^{2\gamma}}{\alpha}\right)^{-\alpha}
+  k(x,x';\alpha,\gamma) = \left(1+\frac{\|x-x'\|^{2\gamma}}{\alpha}\right)^{-\alpha},
 ```
 
+where $\alpha > 0$ and $\gamma > 0$.
+
 ## Polynomial Kernels
 
-### LinearKernel
+### Linear Kernel
 
-The [Linear Kernel](@ref KernelFunctions.LinearKernel) is defined as
+The [`LinearKernel`](@ref) is defined as
 
 ```math
-  k(x,x';c) = \langle x,x'\rangle + c
+  k(x,x';c) = \langle x,x'\rangle + c,
 ```
 
-### PolynomialKernel
+where $c \in \mathbb{R}$
 
-The [Polynomial Kernel](@ref KernelFunctions.PolynomialKernel) is defined as
+### Polynomial Kernel
+
+The [`PolynomialKernel`](@ref) is defined as
 
 ```math
-  k(x,x';c,d) = \left(\langle x,x'\rangle + c\right)^d
+  k(x,x';c,d) = \left(\langle x,x'\rangle + c\right)^d,
 ```
 
+where $c \in \mathbb{R}$ and $d>0$
+
 ## Periodic Kernels
 
-### PeriodicKernel
+### Periodic Kernel
+
+The [`PeriodicKernel`](@ref) is defined as
 
 ```math
-  k(x,x';r) = \exp\left(-0.5 \sum_i (sin (π(x_i - x'_i))/r_i)^2\right)
+  k(x,x';r) = \exp\left(-0.5 \sum_i (sin (π(x_i - x'_i))/r_i)^2\right),
 ```
 
+where $r$ has the same dimension as $x$ and $r_i >0$.
+
 ## Constant Kernels
 
-### ConstantKernel
+### Constant Kernel
 
-The [Constant Kernel](@ref KernelFunctions.ConstantKernel) is defined as
+The [`ConstantKernel`](@ref) is defined as
 
 ```math
-  k(x,x';c) = c
+  k(x,x';c) = c,
 ```
 
-### WhiteKernel
+where $c \in \mathbb{R}$.
+
+### White Kernel
 
-The [White Kernel](@ref KernelFunctions.WhiteKernel) is defined as
+The [`WhiteKernel`](@ref) is defined as
 
 ```math
-  k(x,x') = \delta(x-x')
+  k(x,x') = \delta(x-x').
 ```
 
-### ZeroKernel
+### Zero Kernel
 
-The [Zero Kernel](@ref KernelFunctions.ZeroKernel) is defined as
+The [`ZeroKernel`](@ref) is defined as
 
 ```math
-  k(x,x') = 0
+  k(x,x') = 0.
 ```
 
 # Composite Kernels
 
-### TransformedKernel
+### Transformed Kernel
 
-The [Transformed Kernel](@ref KernelFunctions.TransformedKernel) is a kernel where input are transformed via a function `f`
+The [`TransformedKernel`](@ref) is a kernel where input are transformed via a function `f`
 
 ```math
-  k(x,x';f,\widetile{k}) = \widetilde{k}(f(x),f(x'))
+  k(x,x';f,\widetile{k}) = \widetilde{k}(f(x),f(x')),
 ```
 
-Where `k̃` is another kernel
+Where $\widetilde{k}$ is another kernel and $f$ is an arbitrary mapping.
 
-### ScaledKernel
+### Scaled Kernel
 
-The [Scalar Kernel](@ref KernelFunctions.ScaledKernel) is defined as
+The [`ScaledKernel`](@ref) is defined as
 
 ```math
   k(x,x';\sigma^2,\widetilde{k}) = \sigma^2\widetilde{k}(x,x')
 ```
 
-### KernelSum
+Where $\widetilde{k}$ is another kernel and $\sigma^2 > 0$.
 
-The [Kernel Sum](@ref KernelFunctions.KernelSum) is defined as a sum of kernel
+### Kernel Sum
+
+The [`KernelSum`](@ref) is defined as a sum of kernels
 
 ```math
-  k(x,x';\{w_i\},\{k_i\}) = \sum_i w_i k_i(x,x')
+  k(x,x';\{w_i\},\{k_i\}) = \sum_i w_i k_i(x,x'),
 ```
-
+Where $w_i > 0$.
 ### KernelProduct
 
-The [Kernel Product](@ref KernelFunctions.KernelProduct) is defined as a product of kernel
+The [`KernelProduct`](@ref) is defined as a product of kernels
 
 ```math
-  k(x,x';\{k_i\}) = \prod_i k_i(x,x')
+  k(x,x';\{k_i\}) = \prod_i k_i(x,x').
 ```

docs/src/metrics.md

@@ -1,9 +1,9 @@
 # Metrics
 
-KernelFunctions.jl relies on [Distances.jl]() for computing the pairwise matrix.
+KernelFunctions.jl relies on [Distances.jl](https://github.com/JuliaStats/Distances.jl) for computing the pairwise matrix.
 To do so a distance measure is needed for each kernel. Two very common ones can already be used : `SqEuclidean` and `Euclidean`.
-However all kernels do not rely on distances metrics respecting all the definitions. That's why two additional metrics come with the package : `DotProduct` (`<x,y>`) and `Delta` (`δ(x,y)`).
-Note that all base kernels must have a defined metric defined as :
+However all kernels do not rely on distances metrics respecting all the definitions. That's why  additional metrics come with the package such as `DotProduct` (`<x,y>`) and `Delta` (`δ(x,y)`).
+Note that every `BaseKernel` must have a defined metric defined as :
 ```julia
     metric(::CustomKernel) = SqEuclidean()
 ```

docs/src/userguide.md

@@ -2,7 +2,7 @@
 
 ## Kernel creation
 
-To create a kernel chose one of the kernels proposed, see [Kernels](@ref), or create your own, see [Creating Kernels](@ref)
+To create a kernel chose one of the kernels proposed, see [Base Kernels](@ref), or create your own, see [Creating your own kernel](@ref)
 For example to create a square exponential kernel
 ```julia
   k = SqExponentialKernel()