Tagged Questions
2
votes
2answers
114 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
136 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
73 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
99 views
2
votes
0answers
299 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
152 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
171 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
220 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 ...
5
votes
2answers
184 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
201 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
228 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 ...
