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Summer of Code - Getting Started: Difference between revisions
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{{Note|Do you use Octave at your working place or university? Do you have some numerical project in mind? You are always welcome to '''propose your own projects'''. If you are passionate about your project, it will be easy to find an Octave developer to mentor and guide you.}} | {{Note|Do you use Octave at your working place or university? Do you have some numerical project in mind? You are always welcome to '''propose your own projects'''. If you are passionate about your project, it will be easy to find an Octave developer to mentor and guide you.}} | ||
== Adding regression GAM and kNN classification functionality in statistics package == | |||
Generalized Additive Models and k-Nearest Neighbor algorithms are two important tools in advanced statistics used for regression and classification problems, respectively. The statistics package, although heavily developed during the past year, still lacks any functionality regarding these two algorithms. | |||
The scope is to implement both the respective class def objects as well as the relevant functions in a MATLAB compatible way. | |||
* '''Project size''' [[#Project sizes | [?]]] and '''Difficulty''' | |||
: ~350 hours (medium) | |||
* '''Required skills''' | |||
: Octave, familiarity with statistical methods | |||
* '''Potential mentors''' | |||
: [https://octave.discourse.group/u/pr0m1th3as Andreas Bertsatos] | |||
== ode15{i,s} : Matlab Compatible DAE solvers == | == ode15{i,s} : Matlab Compatible DAE solvers == | ||