- Install the ‘Manopt’ toolbox by following the installation instructions provided on their website: https://www.manopt.org/
- Define your dataset, which consists of samples represented as points on the Grassmann manifold. Each sample should be represented as a matrix, where the columns of the matrix are the data points.
- Compute the discriminant Grassmann kernel matrix using ‘grassmann’ functions provided by the ‘Manopt’ toolbox. These functions typically take the dataset as input and returns the kernel matrix.
- Use the computed kernel matrix as input to your desired classification algorithm to perform classification on the Grassmann manifold.
Is there a Matlab representation for discriminant Grassmann kernels?
5 views (last 30 days)
Show older comments
Is there a Matlab representation for discriminant Grassmann kernels?
0 Comments
Answers (1)
Karanjot
on 8 Nov 2023
Hi,
I understand that you want to know about representation of discriminant Grassmann kernels in MATLAB.
The discriminant Grassmann kernels are a type of kernel function used in machine learning algorithms for classification tasks involving Grassmann manifolds.
Currently, MATLAB doesn’t have an in-built implementation for Grassmann kernels. However, to use discriminant Grassmann kernels in MATLAB, you can utilize a third-party toolbox ‘Manopt’, which is a toolbox for optimization on manifolds. ‘Manopt’ provides a set of functions and tools for working with Grassmann manifolds and computing various operations on them, including the computation of discriminant Grassmann kernels.
Here are the general steps to use discriminant Grassmann kernels in MATLAB:
To learn more about other tools to represent Grassmann kernels, you may refer to the webpages below:
I hope this helps!
0 Comments
See Also
Categories
Find more on Statistics and Machine Learning Toolbox in Help Center and File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!