Questions tagged [k-nearest-neighbors]

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Hierarchical Navigable Small World Graphs : Expected Number of Steps in a Layer

Paper: Efficient and robust approximate nearest neighbor search using Hierarchical Navigable Small World graphs In the Search Complexity section, the author estimates that the expected number of steps ...
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Why the number of training points to densely cover the space grows exponentially with the dimension?

In this lecture (minute 42), the professor says that the number of training examples we need to densely cover the space of training vectors grows exponentially with the dimension of the space. So we ...
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What is the effect of K in K-NN on the VC dimension?

What is the effect of K in K-NN on the VC dimension? When K increases, is the VC dimension decreased or increased, or we can't say anything about this? Is there a reference book that discusses this?
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Is it possible to use k-nearest neighbour for classification with more than two attributes?

If I were to have a dataset of 9 attributes of different types that describe current weather, such as temperature, humidity, etc., and want to classify the current weather by use of a k-NN algorithm, ...
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what is the correct approach for KNN in item based recommendation system?

if I make an application for movies and each user in the system can rate the movies. And I want to make a recommendation system to recommend movies to active user based on his rating for other movies. ...
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How to manually draw a $k$-NN decision boundary with $k=1$ given the dataset and labels?

How to manually draw a $k$-NN decision boundary with $k=1$ knowing the dataset the labels are and the euclidean distance between two points is defined as
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Why is KNNBasic better than KNNWithMeans with the default parameters, but KNNWithMeans performs better with folds?

I'm learning a bit about the use of the Surprise library and I have a set of data with users and ratings. I'm training a network with this library, using KNNBasic and KNNWithMeans, this last algorithm ...
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