# Questions tagged [clustering]

Clustering is the problem of finding groups of data points (often modelled as nodes in a graph) that are closer to each other than to other points.

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### k-means clustered data: how to label newly incoming data

I have a data set with labels that were produced by a $k$-means clustering algorithm. Now there is some data (with the same data structure) from another source and I wonder what is the most sensible ...
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### Finding the “most modular” subset of graph vertices, i.e. that minimize disagreement inside and outside

Let $G = (V, E)$ be a graph. I want to find the subset of vertices of $G$ that minimizes a certain modularity cost. In our setting, the modularity cost of a subset $X$ is defined as the number of ...
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### How is the (local) clustering coefficient defined for vertices with degree 1

We want to compute the clustering coefficient $C$ for an undirected graph $G = (V, E)$. The clustering coefficient $C$ for a graph $G$ is the average over all local clustering coefficients $C_i$, ...
274 views

### Persistent Homology vs Clustering Methods

How do persistent homology and clustering methods for data point clouds differ? I'm specifically interested in the application to gene expression data of cancer patients, but any example works. I ...
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### How to cluster similar objects into fixed size groups?

I have $n$ people each of which can meet on certain days of the week. I want to group them into $\frac{n}{k}$ groups of size $k$ such that all people in a group can meet on a day. eg - Suppose there ...
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### Algorithm to separate single contour of glyph into several strokes?

A glyph contour contains points set {p}, a point contains tuple (x,y,on_curve). Now, think about this need, converting contour of glyph X, for example, into to two contour parts or two strokes, point ...
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### How to map points in high-dimensional space into dense grid in lower-dimensional space?

A formal description of the problem: Given a set $P$ of $n^k$ points in $d$ dimensional space, what algorithm can I use to find a mapping between them and points on a $n \times n \times n...$ grid in ...
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### Document clustering for summarization

I am curious as to what steps one would reasonably need to take to perform an extraction-based text summarizer. I've taken a look at some papers I've found on Google such as this one, which explains ...
38 views

### Algorithms / heuristics for a distributed sorting problem

The setting: There's a cluster of $k$ computers (= nodes). For simplicity, assume their hardware is identical. The network topology can be complicated, but let's simplify and assume it's a clique ...
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### Enumerate subtrees of a given size in a graph

Given a graph $G$ with $n$ nodes, is there an algorithm to find $m$ subtrees, each with $\lfloor n/m\rfloor$ or $\lceil n/m\rceil$ nodes, such that every node of $G$ is in exactly one tree? Other ...
58 views

### How to cluster nodes based on the number of dependencies

I have a problem where, there are a set of nodes and dependencies between them. I want to cluster them based on the maximum number of dependencies. Dependencies can be thought of as number of edges ...
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### Is it possible to represent a citation network as a Tensor for clustering purposes?

My goal is to find a clustering (or an embedding in a vector space) algorithm for a citation network with nodes containing rdf (resource description framework) data (description logic). Dyadic ...
19 views

### Separate overlapping clusters

Suppose I have multiple data points in 2d (x,y) that are either labeled as A, B, C, or D. I find a minimum bounding area for points that are labeled as A and refer to it as cluster A. I can do the ...
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### How can I express the similarity between a Bing and a Google search result?

I'm working on a "semantic" browser engine where all search engines should look the same. One way to do this is to hard-code parsing rules for each site; another is to use machine-learning. Of course ...
28 views

### Divide directed weighted graph into two parts

I have a directed, weighted graph $G = (E,V)$. For example, one might be $|E| = 74000, |G| = 725$. I want to divide this graph into two parts/clusters/communities, taking the edge weights into ...
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### Clustering - Complete Linkage draw example

I'm studying unsupervised learning methods (clustering) and i've seen the Complete Linkage Method. I've also seen the following statement: Unlike single linkage, the complete linkage method can be ...
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### Find shared properties of a cluster samples

I have a dataset which contains ~15 features. With the elbow method, I found out that the optimal number of clusters is probably four. Therefore, I applied the K-means algorithm with four clusters. ...
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### Evaluating clustering/partitioning quality

I'm wondering what are the most common/recognized methods to assess the quality of a clustering. That is because I have developed a tool that can cluster/partition a network (in this case, a public ...
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### Grouping/Clustering results based on shared values

I have a data set that is similar to this: 10,000 jobs with 200,000 applicants which are linked to a job. I'm looking to cluster the shared jobs based on applicants that they share, am I reinventing ...
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### How to perform particle swarm optimization clustering of results obtained from tf-idf vectorizer?

I have a collection of news articles. I have performed tf-idf operations on them. I am using python as programming language so it was just the use of TF-IDF vectorizer function. I now have the ...
18 views

### Cluster with categorical / ordinal

i have a dataset with movies review. I wish cluster my element but inside i have a categorical / ordinal values. i seen that exist: MCA (Multiple Correspondence Analysis) https://www.utdallas.edu/~...
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### Algorithm to group entities into variable sized groups based on attribute

I have the following problem: There are n entities (persons) having a common attribute (weight) and I need to build weight categories (this is for a sports event) grouping people based on their ...
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### What is the relationship between pairwise loss and centroid loss?

What is the relationship between pairwise loss and centroid loss? Under what conditions you would expect them to give similar behavior? Under what conditions would they give different behavior?
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### Clustering non-overlapping time series

I have thousands of times series of different length and different time. I want to group them together so that I know the optimal ones to pick as input for a ML algorithm and to document how they are ...
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### how to add bound to clustering algorithm?

I've got a numeric matrix with 72 rows and 2 columns where the first column is the index value and the other column has sequence from 0 to 5 repeated 12 times. The dataset is like above: ...