LabeliaLabs / distributed-learning-contributivity

Simulate collaborative ML scenarios, experiment multi-partner learning approaches and measure respective contributions of different datasets to model performance.
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Plot data distribution #353

Closed kat-leen closed 2 years ago

kat-leen commented 3 years ago

New plot of the data/ground truth distribution based on the one made by @bowni for the reference scenarios.

Changes :

codecov-commenter commented 3 years ago

Codecov Report

Merging #353 (e9851c7) into master (eb20b80) will increase coverage by 0.38%. The diff coverage is 96.42%.

Impacted file tree graph

@@            Coverage Diff             @@
##           master     #353      +/-   ##
==========================================
+ Coverage   79.48%   79.86%   +0.38%     
==========================================
  Files          15       15              
  Lines        3158     3224      +66     
==========================================
+ Hits         2510     2575      +65     
- Misses        648      649       +1     
Impacted Files Coverage Δ
mplc/scenario.py 80.39% <96.00%> (+0.87%) :arrow_up:
mplc/utils.py 86.71% <96.36%> (+6.03%) :arrow_up:
mplc/experiment.py 83.33% <100.00%> (ø)
mplc/partner.py 93.61% <100.00%> (+0.21%) :arrow_up:

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bowni commented 2 years ago

Well done @kat-leen great addition to the library for much clearer definition and execution of scenarios 👍