October 2017
Beginner to intermediate
270 pages
7h
English
Content preview from Machine Learning for Developers
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Pros and cons of K-NN
The advantages of this method are as follows:
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Simplicity: There's no need to tune parameters
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No formal training needed: We just need more training examples to improve the model
The disadvantage is as follows:
It is computationally expensive - in a naive approach, all distances between points and every new sample have to be calculated, except when caching is implemented.
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