Here is my current to-do list on improvements to be made/features to be added to the core code. Legend: :bangbang: highest priority :exclamation: higher priority :turtle: lower priority/solution is time-intensive - [ ] 1. DataFetcher - [ ] :turtle: 1.1 Automatically scale properly when running over a huge number of histograms (avoid huge memory usage) - [x] 2. Algorithms/training - [x] :bangbang: 2.1 Train only with good runs by default - [x] :bangbang: 2.2 Implement flattening of 2d histograms for PCAs (merge Si's code) - [x] 2.3 Autoencoders - [x] :exclamation: 2.3.1 Make default behavior to train a single AutoEncoder per histogram - [x] :exclamation: 2.3.2 Make algorithms and training configurable through json input (rather than just CLIs) - [ ] 3. Assessment - [x] :bangbang: 3.1 Make SSE histograms for good/bad runs in addition to train/test set - [x] :exclamation: 3.2 Make SSE histograms both in per-events set format and per-algorithm format - [x] :exclamation: 3.3 Plotting of 2d histograms - [x] :exclamation: 3.4 Function for ROC curve plots - [x] :exclamation: 3.5 Function to make summary table of AUC and tpr/fpr values - [ ] :turtle: 3.6 Switch from yahist to boost, mplhep edit: test
Here is my current to-do list on improvements to be made/features to be added to the core code.
Legend:
‼️ highest priority
❗ higher priority
🐢 lower priority/solution is time-intensive
edit: test