Hi Gael
I would say the Seminal Paper is the following
Wrobel, S. (1997). An algorithm for multi-relational discovery of
subgroups. In Principles of
Data Mining and Knowledge Discovery, pages 78{87. Springer.
And more papers are here
Abudawood, T. and Flach, P. (2009). Evaluation measures for m
On Mon, Sep 01, 2014 at 11:38:46PM +0530, Debanjan Bhattacharyya wrote:
> If you type "Cortana Subgroup Discovery" in scholar.google.com, you will get a
> list of papers.
Which is the seminal paper. I get only 15 papers with this query, and
none have much citations.
Cheers,
Gaël
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Hi Gaël
Subgroup Discovery is a well established algorithm.
If you type "Cortana Subgroup Discovery" in scholar.google.com, you will
get a list of papers.
Some more can be seen here http://datamining.liacs.nl/background.html
I think it will satisfy all the conditions mentioned in the link you
p
On Mon, Sep 01, 2014 at 11:01:25PM +0530, Debanjan Bhattacharyya wrote:
> Subgroup Discovery is a great option to bridge the gap here (like we have
> Cortana implemented in Java. Python will be much faster without a doubt.).
> Is there any plan to get this incorporated within sklearn ?
The necess
Hi All
I have been working for a while on sklearn, targeting different real life
machine learning problems. I have experienced there is a large range of
problems were the tree algorithms are not at par, because of the way the
splits are done, (gt and lt) on values. This is specifically applicable
