I'm pretty new to Mahout, but it looks like there aren't any statistical
machine learning algorithms that use Gaussian distributions. Specifically,
I'm thinking of clustering algorithms that use Gaussian distributions to
model clusters and hidden Markov models that use Gaussian distributions.
Can s
K-means uses Gaussian errors. The dirichlet clustering can be configured
to use Gaussian errors.
SVD uses Gaussian errors. QR decomposition can be used to solve problems
with Gaussian errors.
I think I don't understand what you are asking about.
On Fri, May 10, 2013 at 1:10 PM, Matthew McClai
In k-means clustering, the clusters are characterized by their mean
vectors, and data samples belong to clusters according to the distance to
these means. If distance is measured using the L-2 norm (Euclidean
distance), assigning data samples to clusters is equivalent to using
maximum likelihood, w
On Sat, May 11, 2013 at 9:43 AM, Matthew McClain wrote:
> This constraint can be
> removed by characterizing each cluster by the mean and covariance of its
> samples, and using maximum likelihood in place of the distance measurement
> for assigning clusters to samples.
>
Just a note that ordinary
