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Questions tagged [euclidean-distance]

the Euclidean distance or Euclidean metric is the "ordinary" distance between two points that one would measure with a ruler, and is given by the Pythagorean formula.

In mathematics, the Euclidean distance or Euclidean metric is the "ordinary" distance between two points that one would measure with a ruler, and is given by the Pythagorean formula. By using this formula as distance, Euclidean space (or even any inner product space) becomes a metric space. The associated norm is called the Euclidean norm.

http://en.wikipedia.org/wiki/Euclidean_distance

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Computing pair wise distances for metabolic models

I'm working on comparing bacterial metabolic models. Each models consists of a set of metabolites. e.g Model1 - {M1, M2, M3, M4} (M1- metabolite name) Model2 - {M3, M4, M5, M6, M7, M8} I have to compare the difference between these 2…
SriniShine
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Calculate closest Euclidean Distance with JavaScript

I have a dataset which looks like this (Original data is here): var irisjson = [ {"sepalLength": 5.1, "sepalWidth": 3.5, "petalLength": 1.4, "petalWidth": 0.2, "species": "setosa"}, {"sepalLength": 4.9, "sepalWidth": 3.0, "petalLength":…
supaplex
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Random moving from coordinates in Javascript

I'm using Javascript to build my humble robot army. // Objet Robot function Robot(nick, pv, maxSpeed, position) { this.nick = nick; this.pv = pv; this.maxSpeed = maxSpeed; this.position = position; }; //Méthode présentation des…
Moody_jr
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d3.js updating svg.path on drag with euclidean distance

So I've hacked together a few examples to get something similar to what I want - I've been extending it more and more to learn the library. I've run into a problem recently - I can't seem to access a path element on drag. I know what I want to do is…
dom_hutton
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How to find the nearest value in the database

How to look for the nearest value in the database, for example the data in the database for the value of: Data that will be tested is -100, how the system can issue the results of the test -100 is the character A. Private Sub Button4_Click(sender…
MHD
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WEKA classes in map and reduce phases of KMeans Clustering on hadoop

I want to use WEKA's classes inside mapreduce program for performing KMeans Clustering on Instances. I just want an overview for map and reduce classes. How the distance computed by WEKA classes be reviewed in Reducer classes?
Navjot Grewal
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Find whether car assigned is moving toward customer or moving away customer

Data which available for computation is Driver (lat,lon) x mins customer (lat,lon) x - millisecond Driver (lat,lon) x-1 mins Driver (lat,lon) x-2 mins I have set of location in which i want to find the whether car is moving towards or moving…
Syed Abdul Kather
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Combining Euclidian distance by measuring colour and edge distance

Say I have calculated the euclidean distance between two images using colour as a feature and also calculated the distance between the two images using their edges. I want to test to see if combining these two distance values will give a better…
Bad Dub
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R: Clustering customers based on similar product interests for an event

I have a dataset with a list of customers and their product preferences. Basically, it is a simple CSV with a column called "CUSTOMER" and 5 other columns called "PRODUCT_WANTED_A", "PRODUCT_WANTED_B" and so on. I asked these customers if they were…
Ricardo Costa
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Elegant LINQ solution for finding Max/Min/Avg/etc. euclidean disdance between points

Assume I have list of points and I want to find Max/Min/Avg/etc. euclidean disdance between them. Is there elegant LINQ solution? static void Main(string[] args) { List points = new List() { new Point(1, 1), new Point(2, 2), new…
Brans Ds
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Euclidean vs Cosine for text data

IF I use tf-idf feature representation (or just document length normalization), then is euclidean distance and (1 - cosine similarity) basically the same? All text books I have read and other forums, discussions say cosine similarity works better…
Soumyajit
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Python Numpy efficient Polar euclidean distance

I have a list of n polar coordinates, and a distance function which takes in two coordinates. I want to create an n x n matrix which contains the pairwise distances under my function. I realize I probably need to use some form of vectorization with…
Nezo
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How to speedup my Libsvm vector to std::vector conversion?

Introduction I have a libsvm vector of the form: {i_1:v_1; i_2:v_2;...; i_n:v_n} Where i_j:v_j represent respectively the index and the value. If the value is null then it wont be given any index. My objective is to compute the euclidean distance…
Hani Goc
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Apache Mahout - Generating a recommendation using EuclideanDistanceSimilarity

I have been using the Mahout library to implement a recommendation algorithm. I have used the EuclideanDistanceSimilarity class and so far my results seem fine. My DataModel currenty consists of 500 ratings for 100 items which are rated on a scale…
jxs145
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What distances measures perform well on content-based Recommendation Systems?

I want to implement a content based recommendation system that provides a list of recommended books based on user input. I`ll be using TF-IDF to determine how important a word is to a given book and will create a Book Characteristic Vector for…
John Constantine
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