I want to join Gaël in thanking you for saying thanks.
It's great to see appreciation of the work that the scientific python
community does.
I don't think I've seen anyone cite scipy in their research work, even
though it is the backbone for so many papers.
It's important for us that the academic environment recognizes software
contributions, because many
of us rely on academic funding to do this work.
Best,
Andy
On 03/22/2017 01:10 AM, Brown J.B. wrote:
To all organizers, developers, and maintainers involved in the
Scikit-learn project,
I would like to share a recent article that researchers from MIT, ETH,
and Kyoto University (myself) have published about building efficient
models for drug discovery and pharmaceutical data mining.
In short, it demonstrates through replicate experiment that neither
big data nor complex AI such as deep learning are necessary for
efficient drug discovery, and that active learning can guide/assist
decision making processes in the real world.
The paper's success is underpinned by the use of Scikit-learn's
RandomForestClassifier implementation combined with other techniques
developed in the work.
Therefore, it is a by-product of the volunteerism, hard work, and
dedication by those involved in scikit-learn.
As the senior author of this study, I wish to share my great
appreciation for your efforts.
While I am strongly limited in time and can barely contribute to this
community, I cannot thank all of you enough for your work - it has
made an impact.
We are working on theoretical extensions of the work now, as well as
pushing the technology forward in applied discovery sciences (in
agricultural, pharmaceutical, and medical areas). In the theory and
real-world applications, scikit-learn is indispensible.
We have made the paper open access, and hope that such will inspire
this community as well as those in applied sciences.
You will see that the open source software community has been listed
in the Acknowledgments.
Certainly, we would welcome even the most casual of comments about the
paper.
The paper can be retrieved from here:
http://www.future-science.com/doi/abs/10.4155/fmc-2016-0197
With kindest regards and sincere appreciation,
J.B. Brown
Kyoto University Graduate School of Medicine
Junior Associate Professor and Principal Investigator
http://statlsi.med.kyoto-u.ac.jp/~jbbrown
<http://statlsi.med.kyoto-u.ac.jp/%7Ejbbrown>
PS - To those of you involved in the matplotlib, scipy, and numpy
projects, your forwarding of this to those projects would be
appreciated. They were also critical.
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