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/* This file is part of the Gudhi Library. The Gudhi library
* (Geometric Understanding in Higher Dimensions) is a generic C++
* library for computational topology.
*
* Author(s): Mathieu Carriere
*
* Copyright (C) 2017 INRIA
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef DOC_KERNEL_INTRO_KERNEL_H_
#define DOC_KERNEL_INTRO_KERNEL_H_
namespace Gudhi {
namespace kernel {
/** \defgroup kernel Kernels
*
* \author Mathieu Carrière
*
* @{
*
* Kernels are generalized scalar products. They take the form of functions whose evaluations on pairs of persistence diagrams are equal
* to the scalar products of the images of the diagrams under some feature map into a (generally unknown and infinite dimensional)
* Hilbert space. Kernels are
* very useful to handle any type of data for algorithms that require at least a Hilbert structure, such as Principal Component Analysis
* or Support Vector Machines. In this package, we implement three kernels for persistence diagrams: the Persistence Scale Space kernel,
* the Persistence Weighted Gaussian kernel and the Sliced Wasserstein kernel.
*
*
* When launching:
*
* \code $> ./BasicEx
* \endcode
*
* the program output is:
*
*
* \copyright GNU General Public License v3.
* \verbatim Contact: gudhi-users@lists.gforge.inria.fr \endverbatim
*/
/** @} */ // end defgroup kernel
} // namespace kernel
} // namespace Gudhi
#endif // DOC_KERNEL_INTRO_KERNEL_H_
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