# Tagged Questions

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### Probability distribution of distances to micro-cluster centers using particle filtering

Is it possible, using particles filter, to get the probability distribution of distances to cluster centers in an online clustering process, where for each data-point x, if x is close enough to its ...
134 views

### Choosing which data-point to label (active learning)

For an online unsupervised learning algorithm, data-points are learned sequentially. The performance may improve if in addition to the unlabelled data we have some labelled data-points (i.e. ...
202 views

### An incremental Gaussian mixture model

Question 1: Suppose that data is modelled by a mixture of K probability distributions which are actually Gaussians. $P(x_i|\theta_j)$ is the probability density of the j'th cluster, for which the ...
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### Document image analysis and retrieval with online incremental clustering

Is there any interesting problem in the area of "Document Image Analysis and Retrieval" which by nature needs an online/incremental clustering process ? The problem may be in the context of "Logical ...
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### Incremental hierarchical clustering

I have an online k-means algorithm following this scheme: ...
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### Distance threshold for clustering

Usually online clustering methods (based on kmeans or not) define a distance threshold value. If a new data-point $x$ is far enough from the nearest center $c$ (i.e. the distance from $x$ to $c$ is ...
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### Finding communities in online social networks by removing nodes

I want to carry out Graph Clustering in a huge undirected graph with millions of edges and nodes. Graph is almost clustered with different clusters joined together only by some nodes (kind of ...
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### clustering with particle filters

Suppose we want to cluster a data stream of unknown number of clusters, and estimate them using particle filters. With particle filters, we need to know $P(x_t | x_{t-1})$ and $P(z_t | x_t)$ (where z ...
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### Sequential clustering with an unknown number of clusters

Is there any clustering algorithms that: does not assume the number of clusters to be known, and processes the data in only one pass by considering it as a continuously arriving data stream (and we ...
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### Online clustering

I'm trying to build a K-means clustering system with 'online learing', that is, there are existing K clusters and data points in them, and periodically there is a new data point that is sent to an ...