/Support-Vector-Machine-Implementation

Our Project for the Theoretical Foundations Of Machine Learning course taken during fall 2023 semester.

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Support Vector Machine Implementation

Our Project for the Theoretical Foundations Of Machine Learning course taken during fall 2023 semester.

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Implementing the support vector machine algorithm that performs the following tasks:

  1. Train and classify for linearly separable case.
  2. Train and classify for the non-separable case.
  3. Train and classify for non-linearly separable case. [Using Kernels]

In each of the previous three cases:

  • Find optimal alphas.
  • Calculate W & b .
  • Formulate the classifier Function.
  • Draw the decision boundary.
  • Use an appropriate dataset for each case.
  1. Performs analysis based on the VC-dimensional and generalization error.