That looks like it should do the trick, thanks to you both,
Martin
On 3 April 2012 12:37, Lars Buitinck wrote:
> Op 3 april 2012 00:51 heeft David Warde-Farley
> het volgende geschreven:
> > You might try representing it as a sparse bag-of-words, i.e. a sparse
> matrix
> > of 100,000 x (severa
Op 3 april 2012 00:51 heeft David Warde-Farley
het volgende geschreven:
> You might try representing it as a sparse bag-of-words, i.e. a sparse matrix
> of 100,000 x (several million), where each row contains a 1 in positions
> where a feature is present and 0 otherwise. Such a representation sho
On Mon, Apr 02, 2012 at 08:19:49PM +0100, Martin Fergie wrote:
> Hi,
>
> I need to cluster some integer data where the features are an unordered
> set, that is the two features
> [20, 1, 10] and
> [ 1, 20, 10] are equivalent and should be in the same cluster.
>
> I think this is essentially simil
Hi,
I need to cluster some integer data where the features are an unordered
set, that is the two features
[20, 1, 10] and
[ 1, 20, 10] are equivalent and should be in the same cluster.
I think this is essentially similar to association rule data mining. Does
anyone know how this can be achieved u
