Statistical Analysis Stack Exchange
Statistical Analysis Stack Exchange

Questions tagged [fuzzy-c-means-clustering]

Fuzzy c-means (FCM) is a clustering algorithm related to k-means. It differs principally in allowing points to belong to more than one cluster.

Steps:

1) Choose a number of clusters.

2) Assign coefficients randomly to each data point for being in the clusters.

3) Repeat until the algorithm has converged (that is, the coefficients' change between two iterations is no more than the sensitivity threshold

  • Compute the centroid for each cluster.
  • For each data point, compute its coefficients of being in the clusters.

Resources:

1) https://en.wikipedia.org/wiki/Fuzzy_clustering#Fuzzy_C-means_clustering

2) https://home.deib.polimi.it/matteucc/Clustering/tutorial_html/cmeans.html

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What ever happened to Fuzzy Logic?

Fuzzy logic seemed like an active area of research in machine learning and data mining back when I was in grad school (early 2000s). Fuzzy inference systems, fuzzy c-means, fuzzy versions of the various neural network and support vector machine…
Skander H.
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In which case does FCM membership converge to 1/K?

I have tested the fuzzy C-means (FCM) algorithm using the R function fanny from the cluster package and I have wrote my own FCM algorithm to have more control on the distance function. The problem is that my final membership function converges many…
sirus
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Stability Index for Fuzzy c Means Clustering in R

I am looking for a stability measure/index for Fuzzy C Means Clustering in R. Can anyone direct me to a package or a code in R? I am not looking for internal indices, only stability measures.
Kitty123
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Are there any conditions on the data in Fuzzy c-mean clustering?

I want to cluster a graph using the FCM algorithm, I used the adjacency matrix of the graph as the data, and the "Euclidean" distance as metric. The problem is that the adjacency matrix is full of zero's (depends actually on the degree of the node)…
sirus
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Is it fair to compare latent Dirichlet allocation to c-means clustering?

I'm trying to think of a good way to explain latent Dirichlet allocation (LDA) to an audience that knows a decent amount about clustering, but nothing about text analysis. Is it fair to draw a comparison between LDA and fuzzy c-means clustering (not…
Josh
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Does the Membership Matrix of Fuzzy C-Means Clustering contain probabilities or degrees of membership?

I recently heard a lecture on Fuzzy C-Means Clustering that stated that the Membership Matrix contains probabilities that particular data points are members of particular clusters. I was confused by this because in "standard" Fuzzy Logic, degree of…
EJoshuaS - Stand with Ukraine
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Unsupervised soft clustering methods

I have a D-dimensional dataset composed of exactly two clusters (this is known) for which I have no labels; the clusters can potentially be wildly imbalanced. I'm after a soft (or fuzzy) clustering method to assign probabilities to each element of…
Gabriel
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Clustering methods recommandation

I tried to use K-means clustering method to create a plot based on the dataset below. The point I was trying to prove is there's non linear relationship between Uploads and Subscribes. If you look at the x-axis of the attached plot below, the more…
Leo
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Fuzzy clustering on non time-series data and the Mfuzz package

I am trying to apply the fuzzy clustering on a dataset that does not have the time series format. I read some documents about the fuzzy c-means and the package Mfuzz in R. As to my understanding, the Mfuzz package is exclusivity to time series data.…
liverpool29
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what`s the name or meaning of this clustering algorithm?

I have been learning the fuzzy clstering algorithm recently,and I got an object function as following: \begin{array}{l} \min \;\;J = \sum\limits_{i = 1}^N {\sum\limits_{k = 1}^K {\sum\limits_{j = 1}^N {{u_{ik}}{d_{ij}}{u_{jk}}} + T\sum\limits_{i =…
Joey.Sh
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fuzzy rule extraction using fuzzy c-means

I have read an article which is about implementing classification methods using fuzzy-inference. It has used c-means, in one of its parts, for extracting fuzzy-rules. It says we have a fuzzy-rule per cluster. (In fuzzification section) Actually, I…
Captain
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About the relation between fuzzy c mean and parametric classifier

Our master said about the relation between the fuzzy c mean and the below equation in the Fukunaga eBook (page 143) about parametric classifier: But , I don't get it, So i asked here to understand it better. If possible, introducing some YouTube…
Soheil Paper
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How to cluster points spatially using a maximum radius as a constraint?

I am building an app to optimize video packet sharing between users that are watching the same video stream at the same time. I do not want to have to guess the number of clusters up front because I don't think I can create a quality guess for…
Robert Oschler
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fuzzy hierarchical clustering

From the Fuzzy C-Means point of view: Every data point belongs to all the cluster which is given by their degree of membership to each cluster. How do I view it in the case of Hierarchical Clustering? How will the membership matrix be like at every…
Jerry
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How to combine Fuzzy C-means clustering and Support vector regression for building a hybrid model FCM-SVR in R?

I have read one article and found that they used the Fuzzy C-means clustering algorithm and support vector regression for building the FCM-SVR predictive model. I see they split the data into 3 clusters by FCM. Then, each cluster builds an SVR…
Hoang Nguyen
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