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Advances in computational geometry and machine learning that offer new methods for search, regression, and classification with large amounts of .
Nearest neighbor is the simplest and fastest implementation of image scaling technique. . Nearest neighbor is a no if, up down scaling algorithm. .
The nearest neighbor algorithm and the closely related repetitive nearest neighbor algorithm is a greedy algorithm for finding candidate solutions to the .
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In pattern recognition, the k-nearest neighbor algorithm (k-NN) is a method for classifying objects based on closest training examples in the feature space. .
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Jul 10, 2008 . Excerpt from The Algorithm Design Manual: The need to quickly find the nearest neighbor to a query point arises in a variety of geometric .
The site dedicated to demo applets of various spatial structures.
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Nearest-neighbor interpolation (also known as proximal interpolation or, in .
Nearest neighbor analysis examines the distances between each point and the closest point to it, and then compares these to expected values for a random .
Nearest-neighbor classifiers are very simple to design (all you have to do is get a database of examples), and often equal or exceed in accuracy much more .
Jan 28, 2010 . In the nearest neighbor problem a set of data points in d-dimensional space is given. These points are preprocessed into a data structure, .
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In k-nearest-neighbor classification, the training dataset is used to classify each member of a "target" dataset. The structure of the data is that there is .
Apr 4, 2011 . These are the set of nearest neighbor parameters for RNA folding compiled by the Turner group in 1999. The parameters are for estimating .
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Slides of tutorial, bibliography, list of related researchers, open problems in similarity search area.
Mar 25, 2011 . Definition of nearest neighbor, possibly with links to more information and implementations.
One strategy for solving the traveling salesman problem is the nearest-neighbor algorithm. Simply stated, when given a choice of vertices this algorithm .
Apr 23, 2010 . K-nearest-neighbor (kNN) classification is one of the most fundamental and simple classification methods and should be one of the first .
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This program performs fast dense K Nearest Neighbor classification. It can be used to train a model and produce an ROC curve based on a testset or k-fold .
May 18, 2011 . The nearest neighborhood problem involves identifying the locus of points lying nearer to the query point than to any other point in the set .
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To demonstrate a k-nearest neighbor analysis, let's consider the task of classifying a new object (query point) among a number of known examples. .
A class representing nearest-neighbor interpolation. Since nearest-neighbor interpolation is simply pixel copying, and not really interpolation at all, .
Nearest Neighbor Interchange is a tree topology search strategy which attempts to improve the likelihood of a given tree by performing the following .
May 14, 2011 . NASA has created a new interactive web-based tool that incorporates observations from past and current lunar missions creating one of the .
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Specify 'kNN', the number of nearest neighbors to consider, and press 'Classify' in step 3. The classification result map will be displayed on the lower .
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Nov 4, 2002 . Although nearest-neighbor can be efficiently implemented with a Vornoi diagram, I took the brute force approach. This method computes the .
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Feb 6, 2010 . If you want to contribute bug-fixes or enhancements to the Nearest Neighbor Image Unit, the easiest way to do that is to clone the Mercurial .
Nearest neighbor may refer to: Nearest neighbor search in pattern .
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The Nearest Neighbor Rule: A Short Tutorial. Presented by: Philippe Simard and Marcel Mitran. For the course: Pattern Recognition (308-644) .
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May 13, 2011 . NASA has created a new interactive web-based tool that incorporates observations from past and current lunar missions.
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