Questions tagged [self-organizing-maps]

SOM is a kind of neural network used for clustering unlabeled data.

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Differences between t-SNE and SOM

I have some high dimensional data and I want to reduce it to 2 dimensions for visualization. The goal is to color the points in this 2D space to see whether there is any clustering due to different ...
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What is the main differences between choosing hexagonal grid and rectangular grid for SOM?

While I'd expect people to answer this question by saying 'depends on the distribution of data', but what are the thumb rules for deciding which grid to use (either hexagonal or rectangular) for ...
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Kohonen SOM for high (50-100) dimensions

Does a Kohonen-style SOM, using Euclidean distance, work as well as, better than, or worse than alternatives (K-means, etc) in high (50-100 or more) dimensional space? EDIT: I'm thinking particularly ...
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Choosing a Sample Size for a SOM Cluster

Is there an accepted formula to determine a good lower bound for the number of samples needed for the initial input on an SOM clustering algorithm? For example - If I know that there are X number of ...
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Similar to Self Organization Maps, are all other clustering algorithms “self organizing”?

From my understanding of the terms: Self means: No supervision is required during training. Organizing means: To create a topographic ordered map by using unsupervised competitive learning and ...
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1answer
247 views

How to calculate explained variance of Self Organizing Map

Learning SOM recent days, but getting curious how does the explained variance of SOM is calculated. All the articles I have seen ignore this topic. Can anyone give some ideas?
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406 views

SOM - which topological error and average distance are acceptable?

I have calaculated a SOM (with the kohonen package in R, 18x18 heaxagonal grid, 500 iterations, 92 variables, 1189 cases) and am currently trying to access it's usability. Calling a functions for ...
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1answer
66 views

Number of neighbors as a function of dimension

I apologize in advance for perhaps an imprecise formulation of the question. If I have a point in 1D, it has precisely 2 nearest neighbors independent of choices. In 2D, if I allow arbitrary ...
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299 views

Cluster validation method for no cluster labels and differently sized clusters

I'm primarily a programmer and have little to no training in formal maths or statistics of any kind. I'm working on my dissertation (which foolishly is about clustering data), the process is ...
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SOM with unlabelled data for clustering

Hello Id like to know if it's possible to train SOM in unlabelled data. As it's a clustering algorithm. My doubt is, I see people applying it in iris data set which ...
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13 views

SOM self organising maps, how the neighbors are affected misunderstanding

I understand how SOM is similar to Kmeans clustering, but what is not clear to me is the interaction with the neighboring centroids in the connected lattice. All I see in explanations is that the ...
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38 views

Self organized maps on mixed dataset (categoricals / numerics features )

i have a dataset of mixed variables and i want to apply self organized maps on it how can i extend som to mixed dataset? can i use the gower distance instead of euclidienne distance in order to ...
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What cluster algorithm, software, coding language (or a database) does to use to cluster a continued time series?

I have 3 years of continued data of time series in 5 min time interval - 50k rows. I have extracted a list of 1561 samples from the data, defined by exact mathematical conditions. Each record has just ...
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What is the time and space complexity of a standard SOM algorithm?

I am trying to understand the time complexity of a standard SOM algorithm. Given D dimensional Input, a total of N inputs, over a set of E epochs and for an M*M sized map, what would be the complexity?...
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Cluster Events of specific time window

i specify a timewindow of some minutes and extract occurences of certains events. The resulting matrix will look like this: ...
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27 views

Self Organizing Maps - Mapping a single vs more layers

Suppose we train a Self Organizing Map (SOM) with two input layers, meaning we have the following situation: We have a vector $x=(x_1,...,x_n)\in\mathbb{R}^n$ which could represent biometric ...
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1answer
38 views

Partitioning of a Self Organizing Map (SOM) in n clusters

I created the following 9x9 SOM (yellow = small distance between two neurons, red/black = large distance): I know that I can regard each neuron as a separate cluster and that neurons with small ...
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19 views

error in runing SOM

I am trying to run a SOM for my both qualitative data in five-levels (1-5) and quantitative data for 23 variables. unfortunately, I got this error SOM set.seed(222) g <- somgrid(xdim = 4, ...
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1answer
348 views

How to inform the space and time complexity of K-means, SOM and Hierachical clustering

In the paper I am writing, one of the reviewers asked for an "a simple computational complexity analysis or time computational demands of their method" My question is : Can I simply report the ...
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1answer
151 views

One-hot encoding for SOM

I have a question regarding how I should convert categorical data to numerical data. I'm using this kdd99cup intrusion detection dataset, which has a 41 attributes and class label is the type of ...
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1answer
153 views

What is the difference between these distances in self organized maps

I am building an anomaly model and am confused between these distances below. What is the difference between these distances in self organized maps. som.iris$distances dist(som.iris$codes[[1]]) As ...
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1answer
33 views

Self-Organizing maps : is a N*M grid the same as a M*N grid? (with M different from N)

Self-Organizing maps : will a N*M grid give the same results as a M*N grid? (with M different from N)?
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2answers
66 views

Clustering with Self Organizing Maps including time, date and month as attributes

I am about to start up a project on pattern recognition in a highdimensional dataset holding information on transactional salesdata for a company. In that manner I have decided to use the method of ...
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1answer
88 views

Self-Organizing Maps clarity

I have spent sometime reading on self organizing maps. However i am still confused around a few areas. Broadly i understand its a visual technique to reduce high dimensional data - using artificial ...