# Questions tagged [unsupervised-learning]

Finding hidden (statistical) structure in unlabelled data, including clustering and feature extraction for dimensionality reduction.

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### How to apply unsupervised classification to spatial data

I am trying to learn how to apply unsupervised classification to spatial data. In near infra red satelite pictures; the ocean is dark and the forest is white. Each pixel in such an image is an ...
218 views

### SOM automated/objective clustering

So as I understand it SOM is primarily a visualization tool and clustering is a logical next step after you construct a SOM from data. Typically, the clustering is subjective in that after looking at ...
2k views

### SOM clustering for nominal/circular variables

Just wondering if anyone is familiar with clustering nominal inputs. I've been looking at SOM as a solution but apparently it only works with numerical features. Are there any extensions for ...
1k views

### How to differentiate two subgroups from a histogram?

I have a set of samples in which I assume there are 2 definite subsets in it. I plotted their values in a histogram and found that there are two distinct modes as shown in the figure below. My ...
2k views

### How can I assess how descriptive feature vectors are?

I am assessing how good different features are for unsupervised classification of a set of objects. For each different feature I test, I have computed a feature vector that describes the object. I ...
17k views

### How to define number of clusters in K-means clustering?

Is there any way to determine the optimal cluster number or should I just try different values and check the error rates to decide on the best value?
11k views

### Clustering procedure where each cluster has an equal number of points?

I have some points $X=\{x_1,...,x_n\}$ in $R^p$, and I want to cluster the points so that: Each cluster contains an equal number of elements of $X$. (Assume that the number of clusters divides $n$.) ...
307 views

### References on semi-supervised LDA

I'd like to perform semi-supervised LDA (Latent Dirichlet Allocation) in the following sense: I have several topics that I'd like to use, and have seed documents that relate to these topics. I'd like ...
578 views

### Recommended method for finding archetypes or clusters

I wish to cluster users together in a database, with each user represented by a number of features that are both discrete and continuous in nature. The aim is to define a small number of archetypal "...
13k views

### Generative vs discriminative models (in Bayesian context)

What are the differences between generative and discriminative (discriminant) models (in the context of Bayesian learning and inference)? and what it is concerned with prediction, decision theory or ...
4k views

### Soft and Hard EM (Expectation Maximization)

What is the difference between soft and hard expectation maximization? EDIT: ok, i've found out this paper: http://ttic.uchicago.edu/~dmcallester/ttic101-07/lectures/em/em.pdf that explain quite well ...