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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51 views

How should i face this graph problem?

The mentioned problem: Cluster Editing Problem. I need to code this problem but i can't understand the algorithm behind it, even when i try to search for resources about graphs into the web; can ...
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49 views

A heuristic for finding the vector that is maximally distant from a set of vectors

I have two sets of vectors: A and B. I want to find the vector Bi in set ...
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71 views

Minimize the sum of diameters of 2-clustering graph

Is there an algorithm with runtime $\mathcal{O}(n^2)$ that for given weighted graph $G$, partition it into 2 cluster $C_1,C_2$ such that sum of diameters of two clusters minimized? I find a paper with ...
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69 views

Formulate a 2-clustering problem in LP

The problem: Suppose there are $n$ points in plane, and we want to partition points into two clusters such that sum of diameter of clusters is minimized. The diameter of cluster is maximum distance ...
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13 views

Does it make sense to use Bayesian Network to understand feature correlation of clusters created with K-means?

My project idea is to create clusters of typical rooms for hotel customers, indicate which rooms are similar to the one they are looking for and let them understand why they are conceptually similar. ...
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10 views

Dimensional reduction of quadtree influence on clustering with dbscan

Let's say we take a quadtree of 50 dimension and apply dimension reduction(Assume the dimension reduction works well). Why does the dimension reduction not influence the clustering with DBSCAN(Mintpts:...
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21 views

Children of internal node in a quadtree with high dimensionality

Let's say for example we have 1000 points and 50 dimensions. And we build a quadtree where each node represents a 50-dimensional box and is divided by splitting the box into smaller boxes that are ...
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19 views

Understanding contradiction in proof of Algorithm for Testing of Clustering of points in metric space in sub-linear time

I am trying to understand this paper, in which (k, b)-clusterability is defined like so: A set $X$ of points in a metric space is (k, b)-diameter clusterable if $X$ can be partitioned into $k$ ...
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20 views

Testing of Clustering of points in metric space in sub-linear time

I am trying to understand this paper, in which (k, b)-clusterability is defined like so: A set $X$ of points in a metric space is (k, b)-diameter clusterable if $X$ can be partitioned into $k$ ...
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29 views

Clustering Formulas for Networks

Consider an undirected, unweighted graph 𝐺=(𝑉,𝐸). I want to compute the clustering coefficient of each node. In the publicly available lecture from stanford, the following formula for computing the ...
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21 views

Euclidean space vs metric space in density clustering algorithms

I'm trying to find out if these algorithm still work if i replace the Euclidean space with metric space defined on the input point set. But i'm having some trouble figuring it out for some of them. I ...
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17 views

Using Restricted Boltzmann Machines for clustering data

I want to use RBMs as a clustering model and the idea is to use an RBM for clustering a 16 class clustering problem with 4 nodes in the hidden layer. The clustering is done by updating the hidden ...
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39 views

Proof of approximation ratio for approximate triangle inequality version of k-center

Consider the standard $k$-center problem i.e find $k$ disks of radius $r$ that cover all points in a point set $P$. This problem has a well known greedy 2-approximation algorithm where you (...
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17 views

How to solve this grouping problem heuristically?

There are $S$ servers in the system. There are also $M$ computers in the system. Each computer shows different efficiencies when they are connected to different servers. Lets say, for computer $m$, ...
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51 views

Initializations methods for lloyds algorithm (Kmeans++ vs Gonzalez)

I'm learning the initialization methods for Lloyd's algorithm. And I have a hard thing finding examples where Kmeans++ works better than Gonzalez and where the reverse is true so Gonzalez works better ...
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21 views

Possible partitions, for k-means problem(k=2)

I have this brute-force algorithm to solve the problem: Generate all possible partitions of P into two subsets of P1 and P2 For each partition P1, P2 generated in Step 1, compute the cost of the ...
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33 views

Hierarchial clustering cannonnical representation?

I have to handle large binary dataset. That is one of the reasons I have to build my own Hierarchical Clustering. As I digged into the algorithms I was surprised and not ;) to find that it is possible ...
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41 views

Optimal clustering with optimal number of clusters as well as max and min cluster size constraints

I need to cluster $N$ data points. I don't know the number of clusters to be formed. It needs to be found optimally. Also, there is maximum and minimum cluster size constraints, where $C_{\max}$ is ...
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32 views

Find Smooth Functions from Discrete Datas

I'm trying to write a algorithm to solve the following problem, which I did not find any related papers: Given a set of discrete data points generated by n unknown smooth functions $f_1(x), f_2(x), \...
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29 views

How to group thousand of data points for each user

I have thousands of data points associated with users. So a single user can have 2000-10000 data points. These data points are identified by contiguous numbers (e.g. all numbers from 0 to 2000). Each ...
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44 views

Is n-dimentional assignment problem for points NP-hard?

We have $n$ sets of $k$ points in $\mathbb R^d$ and we are trying to partition them to $k$ clusters of $n$ points such that from each set every point is mapped to a different cluster and the sum of ...
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35 views

Is there an approximation algorithm for the three-person stable roommates problem?

While there's an algorithm for solving the stable roommates problem, I understand that the three-people-per-room version of that problem, sometimes called the "threesome roommates problem", ...
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50 views

How do I assign homes to hospitals based on locality? (clustering, kmeans?)

I have a large set of $(X)$ hospitals and $(Y)$ homes, where $(Y)$ is much larger than $(X)$, and their respective coordinates. Each hospital can handle any home within a 50 mile radius, and up to 10,...
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19 views

Tips on speeding up hierarchical linkage clustering algorithm

I implemented a hierarchical linkage algorithm for a set of 5,000 points. Each point is defined with a longitude and a latitude. I read about this algorithm here. These are the steps: Compute ...
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1answer
60 views

Group time series events into minimal amount of buckets

I'm trying to efficiently compute events in a time series by grouping them into buckets. My goal is to have as few buckets as possible. The constraint is that events within one bucket are all within a ...
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34 views

Is there an online/offline tool that can perform K-means/median, given an initial centroid from the user?

The types of problems I am trying to solve are as follows: Given a set of co-ordinates such as: (1,2), (3,3), (6,2), (7,1), a value of k such as k=3 and an initial set of centroids such as c1=(2,2) ...
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Separating labelled points with a plane, minimizing label variance

Suppose we have observations with associated labels $\{({\bf x}_1, y_1), ({\bf x}_2, y_2), \dots, ({\bf x}_n, y_n)\}$ where ${\bf x}_i \in \mathbb{R}^d$ and $y_i \in \mathbb{R}$. Can we efficiently ...
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240 views

How does secondary clustering occur in hashing?

One of my friends said me that secondary clustering is the phenomenon occurring when the probe sequence has the same initial value. This definition shows that secondary clustering occurs in linear ...
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39 views

Question in coreset construction fro K-median clustering

I was reading Ke chen's paper about coreset construction for K-median clustering. In this paper, he assumed that $A$ is an $[α, β]$-bicriteria approximation for K-median clustering for some $α, β=O(1)$...
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building a unsupervised learning model to detect suspicious transactions using DBSCAN

I am working for the first time on building a unsupervised learning model to detect suspicious transactions using DBSCAN, Do I train the model on all data columns(Columns like account number, ...
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36 views

How to detect outliers using DBSCAN?

I am working on a Fraudulent Cash Transaction Detection System using DBSCAN and I want to know what is the proper way to identify outliers? Thank you ##Edite## I had a problem how to represent the ...
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38 views

How can I examine the subnetworks of a nearly fully connected graph?

I have an almost fully connected graph in python with roughly 3k nodes and 9M edges. Each node in this graph is represented by a point in R3 and each edge represents the distance between them with a ...
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14 views

How to cluster a dataset in which each data point is composed of a set of 2-dimensional coordinates

I have a dataset with totally $1000$ scenarios, each of which is composed of $5$ users' coordinates $(x_i,y_i), \forall i \in \{1,\dots,5\}$. Now, based on users' coordinates, I want to cluster these $...
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57 views

How to calculate delta Q (modularity increase matrix) in graphs?

I've been trying to implement the Three-stage Algorithm to compare its results with our new proposed algorithm with different datasets than those mentioned in the article. I've succeeded in ...
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858 views

what would be the time complexity of DBSCAN algorithm?

what would be the time complexity of DBSCAN algorithm if we use it for graph(sparse) clustering $O(n^2)$ or $O(n \log{n})$?
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202 views

How to group intervals which overlap by some amount?

I have an algorithm that generates a list of intervals. The algorithm is run m times. Lets mark the intervals as tuples (s1, e1), (s2, e2), .., (sn, en). It is ...
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28 views

Clustering Application with a Huge Number of Clusters

I am wondering if there are any clustering applications in practice where the number of clusters, i.e., the $k$ in the $k$-means problem is very high ($k>50$, optimally $k>200$), if possible ...
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Finding the middle point of the "most populated" area in a set of points?

I'm working on a game-related application, and I'm trying to find the middle point of the most populated area in my map. Example: ...
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50 views

Clustering sets by set difference

Suppose you have $n$ nonequal sets $S_1, \ldots, S_n$ and some constant $0 \le k < n$. The goal of set clustering is to find a partition of the set $\mathbf{S} = \{S_1, \ldots, S_n\}$ such that the ...
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Bounding 0-1 matrix with k unique rows

Problem Statement: Suppose that I have a $0-1$ matrix $A$ (all of the entries are $0$ or $1$). I wish to find the tightest upper bound with $k$ many unique rows. To be more precise, let S denote the ...
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33 views

RPI cluster performance related to network performance

I'm writing my thesis and i have built a RPI cluster, containing 10 nodes which consists of RPI model 3b. I've them connected to two gigabit switches. I don't know the CAT of the cables. They are not ...
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45 views

How to find clusters of a set of points in n-dimensional space that are furthest from unwanted points

I have a list of 25 points and their coordinates in a 512-dimensional space. I have 8 target points and 17 points I need to avoid (the 17 points to avoid also have differences in priority of how ...
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Delivery Clustering based-on Pick-Drop & Driver locations

I'm reading some papers about Delivery Clustering to solve following generic problems: Given N orders (with its Pick-up and Drop location point) and M delivery-man (with his location). We are going ...
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How can one algorithmically define the required amount of centroids in K-Means clustering?

Say I have a dataset of n vectors. These are, by nature, clustered so that there is a significant distance difference between any two points within a cluster and any two points in separate clusters. ...
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How to cluster N sets into N subsets ,so that we can determine which set a point is from by checking its nearest neighbor in aforementioned subsets?

Question 1: Given N sets of points $S_1$ ... $S_n$ (no intersection between $S_i$ and $S_j$ when i != j), I want to find subsets of $S_1$ ... $S_n$ (call them $T_1$ ... $T_n$ respectively) So that ...
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Clustering customer with string data

I'm looking for a customer clustering solution. I have done a lot of research on the machine learning level to find algorithms that could fit my needs but I can't find much information when the data ...
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42 views

Clustering algorithm with specific cluster grouping areas

I'm looking for a way to cluster points in a given space, where clusters form around specific closed, allowed zones of that initial space. Each allowed zone should be surrounded by points of its ...
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Spliting strings into groups of similar strings

I would like to group a list of strings into groups of strings differing by max 1 character: For instance, given: [John, Alibaba, Johny, Alidaba, Mary] I would ...
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Finding fewest strings that cover $\Sigma^n$ up to $R$ edit operations

Let $\Sigma$ be the alphabet, $0<R<n$ be an integer and let $\Sigma^n$ denote the set of all strings of length $n$ over the alphabet. The task is to find the minimum $m$ such that there exist ...
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228 views

Proof for clustering in a network of friendship

Consider an undirected graph $G = (V, E)$ representing the social network of friendship/trust between students. We would like to form teams of three students that know each other. The question is to ...