I'm looking for a clustering implementation with the following features: Support for high-dimensional data. Now I have approximately 160.000 dimensions/features. Be able to manage sparse matrix. ...
Most clustering algorithms I've seen start with creating a each-to-each distances among all points, which becomes problematic on larger datasets. Is there one that doesn't do it? Or does it in some ...
I have a little problem that is making me freaking out. I have to write procedure for an online acquisition process of a multivariate time series. At every time interval (for example 1 second), I get ...
I'm looking for a good algorithm (meaning minimal computation, minimal storage requirements) to estimate the median of a data set that is too large to store, such that each value can only be read once ...