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Being a non parametric model, they are pretty garbage for generalizations outside of the domain of the data they have "seen" and they are also not very data eff
by karthiktharava 8y ago
Being a non parametric model, they are pretty garbage for generalizations outside of the domain of the data they have "seen" and they are also not very data efficient. One area where I have seen success for them is when they are applied to automatic hyper-parameter selection for neural networks.
- 317070 8y agoIt's the opposite, they are very data efficient (compared to neural networks). Also, they are a bayesian method and give some mathematical guarantees. They are computationally expensive though. You can use them in neural nets to do few shot learning [0]. [0] https://arxiv.org/pdf/1802.07535.pdf https://arxiv.org/pdf/1802.07535.pdf or https://arxiv.org/abs/1807.01622 https://arxiv.org/abs/1807.01622