Trending Technology Machine Learning, Artificial Intelligent, Block Chain, IoT, DevOps, Data Science

Recent Post

Codecademy Code Foundations

Search This Blog

SVM: Maximum Margin with Noise in Machine Learning

Linear SVM Formulation
Limitations of previous SVM formulation

  • What if the data is not linearly separable?
  • Or noisy data points?

Extend the definition of maximum margin to allow no-separating planes.

Objective to be minimized

- Minimize
   + C (distance of error points to their correct zones)
- Add slack variable ੬i

Maximum Margin with Noise


 𝛼i's and 𝛽i's are Lagrange multipliers (≥ 0).

Dual Formulation

Find 𝛼1,𝛼2,.....,𝛼m   s.t

Solution to Soft Margin Classification

  • xi with non-zero 𝛼i will be support vectors.
  • Solution to the dual problem is:
(no need to compute w explicitly)

1 comment:

  1. Going to graduate school was a positive decision for me. I enjoyed the coursework, the presentations, the fellow students, and the professors. And since my company reimbursed 100% of the tuition, the only cost that I had to pay on my own was for books and supplies. Otherwise, I received a free master’s degree. All that I had to invest was my time. Innosilicon A11 Pro


John Academy