# stringdot

##### String Kernel Functions

String kernels.

- Keywords
- symbolmath

##### Usage

`stringdot(length = 4, lambda = 1.1, type = "spectrum", normalized = TRUE)`

##### Arguments

- length
The length of the substrings considered

- lambda
The decay factor

- type
Type of string kernel, currently the following kernels are supported :

`spectrum`

the kernel considers only matching substring of exactly length \(n\) (also know as string kernel). Each such matching substring is given a constant weight. The length parameter in this kernel has to be \(length > 1\).`boundrange`

this kernel (also known as boundrange) considers only matching substrings of length less than or equal to a given number N. This type of string kernel requires a length parameter \(length > 1\)`constant`

The kernel considers all matching substrings and assigns constant weight (e.g. 1) to each of them. This`constant`

kernel does not require any additional parameter.`exponential`

Exponential Decay kernel where the substring weight decays as the matching substring gets longer. The kernel requires a decay factor \( \lambda > 1\)`string`

essentially identical to the spectrum kernel, only computed using a more conventional way.`fullstring`

essentially identical to the boundrange kernel only computed in a more conventional way.- normalized
normalize string kernel values, (default:

`TRUE`

)

##### Details

The kernel generating functions are used to initialize a kernel function
which calculates the dot (inner) product between two feature vectors in a
Hilbert Space. These functions or their function generating names
can be passed as a `kernel`

argument on almost all
functions in kernlab(e.g., `ksvm`

, `kpca`

etc.).

The string kernels calculate similarities between two strings (e.g. texts or sequences) by matching the common substring in the strings. Different types of string kernel exists and are mainly distinguished by how the matching is performed i.e. some string kernels count the exact matchings of \(n\) characters (spectrum kernel) between the strings, others allow gaps (mismatch kernel) etc.

##### Value

Returns an S4 object of class `stringkernel`

which extents the
`function`

class. The resulting function implements the given
kernel calculating the inner (dot) product between two character vectors.

a list containing the kernel parameters (hyperparameters) used.

##### Note

The `spectrum`

and `boundrange`

kernel are faster and
more efficient implementations of the `string`

and
`fullstring`

kernels
which will be still included in `kernlab`

for the next two versions.

##### See Also

##### Examples

```
# NOT RUN {
sk <- stringdot(type="string", length=5)
sk
# }
```

*Documentation reproduced from package kernlab, version 0.9-27, License:*