week07Support Vector Machines
7.1Large Margin Classification
it is a more cleaner and more powerful way to learn complex non-linear function
start from logistic regression(classification)
7.2Mathematics behind large margin classification
SVM Decision Boundary: the distance between blue line and green line
7.3Kernels核函数
关于核函数的几个问题:
- 如何选择标记点?
- 如何得到这些标记点?
- 相似度方程是怎么样的?
- 能否用其他核函数来代替高斯核函数?
7.3.1Kernels I
introduction
高斯核函数的相似性
不同thegma对应的核函数图像
7.3.1Kernels II
C is equal to 1/lambda, so
large C == small lambda, which means lower bias, high variance and overfitting
small C == large lambda, which means high bias, low variance and underfitting