# Questions tagged [distance]

Measure of distance between distributions or variables, such as Euclidean distance between points in n-space.

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### Compare similarity or difference of two distributions by the ratio of moments

I'm looking for a measure that measure the similarity of two distributions in the following forms: $$S = \frac{a \mu_1 + b \sigma_1}{a \mu_2 + b \sigma_2}.$$ The above formula I proposed is not ...
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1 vote
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### Earth Mover (Wasserstein) distance for ordinal discrete data

I am doing data analysis for my Masters research and which includes some Likert scale type questions. I have been calculating some distances between the responses for these questions. All this has ...
1 vote
591 views

### Euclidean distance between points in PCA space along different principal component dimensions

I've picked up this project half way through, and I'm working through the last guy's code, so please bear with me. So the original data consists of 500+ points in 150 dimensions, and I want to ...
26 views

### Measuring distances between distributions of ordinal variables

I'd like to be able to measure how "different" two distributions of ordinal (but not interval) variables $X$ and $Y$ are. Given three random variables $X$, $Y$, $Z$ I'd also like to be able ...
171 views

### What is the maximum number of dimensions in MDS?

If I have an arbitrary Euclidean distance matrix $D=(d_{ij}:i=1,\ldots, I; j=1,\ldots, I)$ and I want to reconstruct its elements (pairwise Euclidean distances) via classical Euclidean MDS. That is ...
1 vote
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### R adjusted cosine similarity [closed]

I would like to find an effective way to get adjusted cosine similarity for a large matrix (10k rows). Apply seems also slow... Could you please suggest a method? Maybe based on the approaches ...
13k views

### What's the maximum value of Kullback-Leibler (KL) divergence

I am going to use KL divergence in my python code and I got this tutorial. On that tutorial, to implement KL divergence is quite simple. ...
1 vote
63 views

### What are the downsides of using euclidean distance for hierarchical clustering of a correlation matrix?

Apologies if this has been answered elsewhere, but I couldn't find any answers discussing this specific question. I am lacking some notion on clustering using euclidean vs correlation distance, when ...
1 vote
221 views