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由于高维映射使得VC维增加,此时,若数据样本个数N有限时,就容易造成过拟合(Overfitting)。
1. What is Overfitting?
Overfitting 产生的原因(老师举了驾车的例子):
2. The Role of Noise and Data Size
当数据样本有限(甚至比较少)时,简单模型比复杂模型性能更优!
3. Deterministic Noise
两类误差:1)数据样本的误差;2)模型表示能力不足带来的误差,如50维的多项式用一个20维的多项式去表示,造成表示不足的误差!
Deterministic Noise
4. Dealing with Overfitting
All very practical techniques to combat overfitting!
Correct the label (data cleaning);
Remove the example (data pruning);
Possibly helps, but effect varies!
Add virtual examples by shifting/rotating the given digits (data hinting);
Possibly helps, but watch out —virtual example not i.i.d. $\sim$ $P(x; y)$!
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