OK, got your points, thanks Ferrel and Peng.
On Sun, Sep 21, 2014 at 11:39 PM, Pat Ferrel pat.fer...@gmail.com wrote:
@li
Mahout down-samples the input data based on how “important” the
cooccurrence of interactions seems to be. I’d use SIMILARITY_LOGLIKELIHOOD
for the best measure of this.
Hi,
I am currently working on a project that
needs categorization of documents (UN-structured data) based on internal
context of document. I am using Apache mahout clustering solution for the
same. So far we have explored Kmeans, Canopy with Kmeans, We have also used
Lucene
Hey, I've just begun working with Mahout and I'm having trouble with very
basic stuff.
So, essentially, I want to use the common iris.csv data and classify it
using the LogisticRegression classifier.
I'm having trouble in going about the whole vectorization, as the features
are integers and the
On 09/23/2014 07:48 AM, Ted Dunning wrote:
On Mon, Sep 22, 2014 at 8:13 AM, Bart Vandewoestyne
bart.vandewoest...@telenet.be wrote:
14/09/22 17:05:01 INFO mapreduce.Job: Task Id :
attempt_1410945757266_2536_m_00_0, Status : FAILED
Error: java.lang.NumberFormatException: For input string:
Name suggestions are appreciated but this is meant to be about the similarity
engine (search engine) recommender.
Recently Lucidworks (the Solr people) announced Fusion, a closed source
extension to the Lucidworks offering. It includes a recommender API, which
makes it easier to deal with
Hi,
I was wondering if would be possible to support bm25 term weighting
extending Mahout's tf-idf implementation.
I was curious to know if anyone here has already tried to do so.
If not, what would be your suggestion for such implementation on Mahout?
Arian Pasquali
Should be pretty easy. I haven't heard of anyone doing it.
Sent from my iPhone
On Sep 23, 2014, at 18:53, Arian Pasquali ar...@arianpasquali.com wrote:
Hi,
I was wondering if would be possible to support bm25 term weighting
extending Mahout's tf-idf implementation.
I was curious to
Lucene 4.x supports okapi-bm25. So it should be easy to implement.
On Tue, Sep 23, 2014 at 11:57 PM, Ted Dunning ted.dunn...@gmail.com wrote:
Should be pretty easy. I haven't heard of anyone doing it.
Sent from my iPhone
On Sep 23, 2014, at 18:53, Arian Pasquali ar...@arianpasquali.com
