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EPISODE · Jul 24, 2015 · 8 MIN
[MINI] k-Nearest Neighbors
from Data Skeptic
This episode explores the k-nearest neighbors algorithm which is an unsupervised, non-parametric method that can be used for both classification and regression. The basica concept is that it leverages some distance function on your dataset to find the $k$ closests other observations of the dataset and averaging them to impute an unknown value or unlabelled datapoint.
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[MINI] k-Nearest Neighbors
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Frequently Asked Questions
How long is this episode of Data Skeptic?
This episode is 8 minutes long.
When was this Data Skeptic episode published?
This episode was published on July 24, 2015.
What is this episode about?
This episode explores the k-nearest neighbors algorithm which is an unsupervised, non-parametric method that can be used for both classification and regression. The basica concept is that it leverages some distance function on your dataset to find...
Can I download this Data Skeptic episode?
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