k-Nearest Neighbor
CS231n课程笔记翻译：图像分类笔记（上）
CS231n课程笔记翻译：图像分类笔记（下）
文章目录
1 With N examples, how fast are training and prediction?
- Train O(1)
- predict O(N)
This is bad: we want classifiers that are fast at prediction; slow for training is ok.
2 hyper-parameters（choices about the algorithm that we set rather than learn）
- What is the best distance to use?
- What is the best value of k to use?
3 k-Nearest Neighbor on images never used
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Very slow at test time
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Distance metrics on pixels are not informative
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Curse of dimensionality（维数灾难）
维数越高，需要填充的样本指数级增长