Summer of Code - Getting Started: Difference between revisions

Summer of Code - Getting Started (edit)

Revision as of 15:57, 24 January 2024

331 bytes added , 24 January

→‎Adding Classification classes and methods in statistics package

Pr0m1th3as

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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. Please note that for such a proposal to be successful it will almost certainly involve initiating pre-proposal discussion over at the [https://octave.discourse.group Octave Discourse forum].}}
-== Adding regression GAM and kNN classification functionality in statistics package ==
+== Adding more Classification classes and implementing missing methods 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.
+Although a ClassificationKNN class was added in the latest statistics release (1.6.1), it still lacks several methods (only `predict` is available at the moment). This GSoC project aims at implementing more methods, such as crossval, cvloss, lime, loss, margin, partialDependence, plotPartialDependence, etc., as well as adding more classdefs related to classification classes, such as ClassificationGAM, ClassificationDiscriminant, ClassificationSVM, ClassificationNeuralNetwork, ClassificationNaiveBayes, etc. The statistics package, although heavily developed during the past years, still lacks a lot of classdef functionality. The scope is to implement classification class def objects and their relevant methods in a MATLAB compatible way.
-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)
+: ~350 hours (hard)
 * '''Required skills'''
-: Octave, familiarity with statistical methods
+: Octave, classdef, good knowledge of statistical methods
 * '''Potential mentors'''
 : [https://octave.discourse.group/u/pr0m1th3as Andreas Bertsatos]