Cousera机器学习基石第六周笔记 Machine Learning Foundation Week 6 Note in Cousera

1 min

Theory of Generalization

test error can approximate training error if there is enough data and growth function does not grow too fast

Restriction of Breaking Point

The Four Breaking Points

growth function m_\H(N)

number of dichotomies

  • positive rays: m_\H(N)=N+1
  • positive intervals: m_\H(N)=\frac{1}{2}N^2+\frac{1}{2}N+1
  • convex sets: m_\H(N)=2^N
  • 2D perceptrons :m_\H(N)<2^N in some cases

Restriction of Breaking Point

Bounding Function
Cases

Bounding Function