Experiment02

[enryH]

• consolidate experiment 02 notebooks
  • move bullets points with tasks to issues
  • make model specific issues with ideas for evaluating them
  • make it work as a script with parameters
  • put more code into configuration files
  • add some more tests for important classes/functions
• Select training data for performance comparisons
  • Entire data PCA, t-SNE, UMAP -> find a cluster of samples
  • fix data, describe it, order it (500-1000 samples for training, validation and testing data)
• Compare different setups and performances
  • On fixed data, create performance difference plots between models, etc
• denoising evaluation