Hello Andreas
Hello Michael
First, I'm happy to be selected as this year's scikit-learn student, and
hope to make a great work.
According to my timeline
<https://github.com/scikit-learn/scikit-learn/wiki/GSoC-2015-Proposal:-Metric-Learning-module#april-27th--may-24th>,
I'm going to use community bonding period to get a clear understanding of
algorithms I decided to implement, so I'll start warm.
The first step was to write a brief description of all three methods
without too much details. Here's my blogpost
<http://barmaley-exe.blogspot.ru/2015/05/introduction.html> on it. I mostly
intended to extract the gist of every method, so you don't have to go
though the papers to understand me.
My next plans:
- Design an interface. There's a section on API
<https://github.com/scikit-learn/scikit-learn/wiki/GSoC-2015-Proposal:-Metric-Learning-module#api>
in
my proposal, but I think ITML, for example, may benefit from having
partial_fit.
- Sketch an algorithm in pseudocode for LMNN and NCA. ITML already has
one in the paper.
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