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这一讲主要介绍当数据线性不可分时,通过非线性映射将数据映射到高维特征空间,使得数据在高维特征空间是线性可分的,进而实现机器学习。
1. Quadratic Hypotheses
2. Nonlinear Transform
The Nonlinear Transform Steps:
Nonlinear Model via Nonlinear $\Phi$ + Linear Models
3. Price of Nonlinear Transform
Q-th order polynomial transform:
4. Structured Hypothesis Sets
Structured Hypothesis Sets
linear model first: simple, efficient, safe, and workable!
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