Description:Compute a square kernel matrix from a given matrix.

Usage:`gist-kernel [options] -data <filename>`

Input:

`-data <filename>`

- a labeled, tab-delimited file of data. Missing values are not allowed.

Output:A square, labeled tab-delimited kernel matrix, with dimension N by N, where N is the number of rows in the data file.

Options:

`-kernel <filename>`

- a file containing a list of kernel transformations, one per line. Valid operations are listed below.`-iskernel`

- Specify that the data file contains a kernel, so do not perform the initial scalar product operation.`-rdb`

- Allow the program to read and create RDB formatted files, which contain an additional format line after the first line of text.`-precision <value>`

- Number of digits after the decimal place in the output file. The default value is 4.`-verbose 1|2|3|4|5`

- Set the verbosity level of the output to stderr. The default level is 2.

Kernel transformations:The kernel transformations file specifies on transformation per line. The transformations are carried out on the kernel matrix in the order listed, and may be repeated. Some transformations include a required argument, which appears immediately after the transformation name.

`constant <value>`

- Add a given constant to every element in the kernel matrix.`coefficient <value>`

- Multiply every element in the kernel matrix by the given value.`power <value>`

- Raise every kernel matrix element to the given power.`radial <value>`

- Perform a radial basis transformation of the kernel using the given width.`diagonal <value>`

- Add a given value to every diagonal element in the kernel.`normalize`

- Project each vector onto the unit sphere in the feature space.`center`

- Center each data point in feature space.`diffusion <value>`

- Convert the given kernel to a matrix of Euclidean distances, and run that matrix through a diffusion kernel computation, with the given value as the diffusion constant.

Warning messages:None

Bugs:

- Does not yet implement the radial basis width selection heuristic, nor the asymmetric soft margin heuristic.
- Only creates square kernel matrices.

Gist