Questions tagged [clustering]

For questions related to clustering (a usual unsupervised learning technique).

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Deep Continuous Clustering algorithm - just one output cluster

I use the DCC algorithm to cluster some data. The whole algorithm is available here, but shortly it is: construct mkNN graph of the data points (the connected components of it are the clusters). ...
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22 views

How does Hartigan & Wong algorithm compare to Lloyd's and Macqueen's algorithm in K-means clustering?

As far I know, this is how the latter two algorithms work... Lloyd's algorithm Choose the number of clusters. Choose a distance metric (typically squared euclidean). Randomly assign each observation ...
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26 views

Binary data clustering by Matrix factorization

I have read an article talking about binary clustering using Matrix factorization(see attached), but i would like to understand some optimization concepts: Is it reasonable to use a Frobenius norm in ...
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38 views

Is there a continuous version of clustering? [closed]

Is there a continuous version of clustering? i.e. detecting N peaks on a plane.
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54 views

How to cluster data points such that the number of clusters is kept minimal and each cluster projects well onto a lower-dimensional subspace?

If I want to find a (linear) subspace onto which a data-set projects well, I can simply use PCA. However, often the data can project with much smaller error if I first separate it into a couple of ...
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80 views

Combining clustering and deep learning for computer vision

Is there any recent work on combining clustering approaches (k-means, or gaussian mixture or PGM) with deep learning for computer vision? In particular I'm interested in if anyone has used the first ...
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60 views

Would it be possible to implement the principals of the K means clustering algorithm in a Neural Network

During a Machine Learning course which I have done I have learnt about the K means algorithm. Is it possible to use the principals of K means within a neural network?
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1answer
44 views

Is this dataset with only two features suitable for clustering with k-means?

I am working with the K-means clustering algorithm for unsupervised learning. Is the following dataset suitable for the k-means clustering task or not? Why or why not? The dataset has only two ...
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35 views

How do I approach this problem?

Let's say I have a dataset with multiple types of multiple ingredients (salt1,salt2, etc). Each n-th variation of each ingredient vs flavor may be represented by an n×k matrix that where an ingredient ...
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55 views

How can I group the entries of the network traffic by their similarity?

I have the traffic of my network (with hundreds of entries). Below I am showing only 9 entries. ...
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2answers
56 views

Could clustering be used to parse pdf documents to get headings and titles?

I'm a bit new to AI and I'd like to use some kind of clustering algorithm to solve a problem: I'm trying to parse pdf documents to get headings and titles. I can parse pdf to html and I'm then able ...
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6answers
72 views

How can I cluster this data frame with several features and observations?

How can I cluster the data frame below with several features and observations? And how would I go about determining the quality of those clusters? Is k-NN appropriate for this? ...
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65 views

Neural network to extract correlated columns

I want to use a neural network to find correlated columns in a .csv file and give them as a output. The input .csv file has ...
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19 views

Finding unique faces in a video

I am trying to find unique (distinct) faces in multiple videos files. What is the best way to do that?
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45 views

How is clustering used in the unsupervised training of a neural network?

How is clustering used in the unsupervised training of a neural network? Can you provide an example?
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1answer
37 views

How to detect patterns in salary distribution if we are suspecting malicious distribution based on employee's region?

We are having suspects in salary distribution in our organisation due to employee's region. The data we have is as the following: ...
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64 views

Grey Wolf Optimization - Issue with Dimension [closed]

I'm trying to use the grey wolf optimization (GWO) for texts clustering. I used this code, https://github.com/7ossam81/EvoloPy-NN/blob/master/selector.py I tried using the dimension 30 for the GWO as ...
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20 views

Clustering of very high dimensional data and large number of examples without losing info in dimensions

I'm trying to get a grasp on scalability of clustering algorithms, and have a toy example in mind. Let's say I have around a million or so songs from $50$ genres. Each song has characteristics - some ...
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2answers
107 views

Is unsupervised learning a branch of AI?

From Artificial Intelligence: A Modern Approach, a book by Stuart Russell and Peter Norvig, this is the definition of AI: We define AI as the study of agents that receive percepts from the ...
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2answers
43 views

How can I cluster based on the complementary categories?

K-means tries to find centroid and then clusters around the centroids. But what if we want to cluster based on the complement? For example, suppose we have a group of animals and we want to cluster ...
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1answer
238 views

What is the role of the 'fuzzifier' w in Fuzzy Clustering?

According to my lecture, Fuzzy c-Means tries to minimize the following objective function: $$J(X,B,U)=\sum_{i=1}^c\sum_{j=1}^n u_{ij}^w \, d^2(\vec{\beta_i},\vec{x_j})$$ where $X$ are the data ...
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2answers
226 views

How to compute the number of centroids for K-means clustering algorithm given minimal distance?

I need to cluster my points into unknown number of clusters, given the minimal Euclidean distance R between the two clusters. Any two clusters that are closer than this minimal distance should be ...
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1answer
92 views

What is graph clustering?

There are several (family of) algorithms that can be used to cluster a set of $d$-dimensional points: for example, k-means, k-medoids, hierarchical clustering (agglomerative or divisive). What is ...
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2answers
106 views

How do we know the classification boundaries of the data?

Consider an image classification problem. Conceptually, we then have some high dimensional space where all the images can be represented as points, and having large enough labeled data set we can ...