0
votes
0answers
23 views

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 ...
2
votes
2answers
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. ...
-1
votes
1answer
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 ...
0
votes
1answer
100 views

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 ...
2
votes
2answers
117 views

Incremental hierarchical clustering

I have an online k-means algorithm following this scheme: ...
2
votes
0answers
651 views

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 ...
2
votes
2answers
197 views

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 ...
1
vote
1answer
214 views

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 ...
2
votes
1answer
290 views

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 ...
6
votes
2answers
221 views

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 ...
0
votes
1answer
286 views

Incremental or online or single pass or data stream clustering refers to the same thing?

Incremental clustering algorithms Online clustering algorithms Data stream clustering algorithms Single pass clustering algorithms Are the following expressions related? Does some of them include ...
5
votes
1answer
244 views

Bias from increased information in FLAME clustering

I hope this is an appropriate forum for this question...if not, any pointers on a place to ask would be great. If my questions is not clear, please just let me know and I'll try to add ...