<filename>Classification/KernelSVM/regularKernelSVM.py
# -*- coding: utf-8 -*-
"""Kernel SVM for machine learning.

Kernel SVM is basically an SVM (see folder SupportVectorMachine ) which
operates with kernels. Kernels use the inner product to help us transform the
feature space to make it possible for Support Vector Machines to create a good
hyperplane to effectively classify non-linear feature sets.

Example:

        $ python regularKernelSVM.py

Todo:
    *
<filename>Classification/KernelSVM/regularKernelSVM.py
# -*- coding: utf-8 -*-
"""Kernel SVM for machine learning.

Kernel SVM is basically an SVM (see folder SupportVectorMachine ) which
operates with kernels. Kernels use the inner product to help us transform the
feature space to make it possible for Support Vector Machines to create a good
hyperplane to effectively classify non-linear feature sets.

Example:

        $ python regularKernelSVM.py

Todo:
    *
# -*- coding: utf-8 -*-