Questions tagged [clustering]

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

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Cognitive science datasets [closed]

I am looking for an interesting dataset in the field of cognitive science or psychology, analyzable by PCA. Your suggestions will be greatly appreciated. By analyzable by PCA I mean that it contains ...
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2answers
39 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
28 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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25 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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48 views
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64 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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2answers
45 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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0answers
59 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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15 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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41 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
33 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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61 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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2answers
104 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 ...
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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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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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1answer
90 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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186 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
87 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 ...