# Tagged Questions

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### Population specific attributes to pairwise distances: How to choose a distance?

I've collected a lot of data for different populations and I need to convert them into a pairwise distance measure. There are several distances such as , Bray-Curtis and Manhattan distances. My ...
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### How to find almost identical records in dataset using an algorithm (for plotting purposes)?

There are 10 datasets, each contains around 2000 records with 21 features and a binary label. There have been many attempts to clean the data and even showing that there were so many redundant, ...
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### Is it possible to use Hellinger distance for environmental variables?

Here is the problem, euclidean distance is not recommended for datasets with many zeroes (like matrices of species/site), as there is the risk of the abundance paradox (Orloci 1978). Whereas to ...
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### Is the max inner product between an instance and a weight vector shows smaller euclidean distance?

Suppose we have a instance x and weight matrix W like K-means and we try to find the nearest centroid. Is it logical to use dot product to each centroid and take the weight vector giving max dot ...
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### Nonlinear manifold learning and distances between projected points

If I use a manifold learning method to project some data points into a low dimensional space, what will be the distances between the projected points? Can I use Euclidean distance? If the distances ...
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### How to compute a measure of distance between sites with continuous variables?

I have a dataframe with each row being a different site (51 sites), and each column being mean values of a different continuous environmental variable (19 variables). I am trying to calculate a ...
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### Euclidean distance prove [duplicate]

I know that Euclidean distance is a measure that may be used to compute the similarity between two vectors. Given a query q and documents d 1, …, dn, we may rank the documents d 1, …, dn in the ...
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### How to make results using Hellinger distance comparable with Euclidean distance outputs?

I have a two kinds of data for the same geographic region. One is presence-absence data of species (for amphibians, reptiles and birds) and the other has several environmental variables for the same ...
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### K-means Mahalanobis vs Euclidean distance

I currently am trying to cluster "types" of changes on bitemporal multispectral satellite images. I applied a thing called a mad transform to both images, 5000 x 5000 pixels x 5 bands. Each band is a ...
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### Are there methods to learn a projection method into euclidean space, given a set of pairwise distances?

Basically, right now I am trying to do some nearest-neighbour searching on an approach where I don't have points in Euclidean space. To do a nearest-neighbour search currently, I take the query and ...
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### Using a cosine similarity does not work for any dataset

I have a clustering algorithm, where if I use an euclidian distance as similarity, it works well on any dataset. If I replace it by a cosine similarity (see my code bellow), it will give a degenerate ...
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### Euclidean distance is usually not good for sparse data?

I have seen somewhere that classical distances (like Euclidean distance) become weakly discriminant when we have multidimensional and sparse data. Why? Do you have an example of two sparse data ...