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Development plan

documentation, documentation, documentation.
QT app needs to have all its lost features (due to decoupling) restored
confidence bands (1st request from Rucknium)
vector input/output rather than just single point (3rd request from Rucknium), that would represent multiple data sources at the same time
finalize the diff transformation. The reconstruction of predictions is skewed. Most probably the transformation need to be done for the whole series, single threaded, rather than each independently. Uncomment tests!
walk forward validation needs better UI and more consistency regarding data holding (adding data/records instead of replacing them for each validation window)
early stop for the regression of predictors, rather than whole data recalculation
plugin interface for Predictors
plugin interface for Loss Functions
plugin interface for Optimization Goals (todo: prediction score vs. truth, alongside the already coded pred. score vs. baseline)
self defined transforms and scripts
protect against look-ahead bias (series transformations to achieve stationarity, as well as individual vector transformations, to ease the writing of optimized versions of predictors). Mostly done but needs constant verification & auto testing
time scale manipulation (low pass/high pass filters)
seasonal corrections (before the time scale manipulation!)
generate alternative scenarios
networked processing
ASCII plots (simpler than gnuplot)

protect against look-ahead bias: done for IPredictor. Needs work for XForm.
prediction: baseline and advanced
weekly discrete time steps (2nd request from Rucknium). Currently the largest time steps are days. Adding monthly won't hurt either.
optimization methods. Goal = prediction score vs. baseline prediction
walk forward validation
R integration
ACF, PACF & Seasonal Decomposition plots in Python
QT app works under latest Debian and Mac

minimize IPredictor interface by scraping off IDataProvider from GetSymbolName
plot learning curves (across time)
distribution of solutions for Grid Search, just like Monte Carlo.
plot how input parameters change the output variable
HTML reports
better test coverage
debugging methods (plot each transformation individually)
reduce compilation memory usage of URT to enable debugging
QT app still hides weekend data
QT app upgrade to QT6 and QCustomPlot 2
speed up serialization
separate simulator for stationarity optimizations
full CLI. Currently using WX App for all configuration
the seasonal decomposition plot is definitely reversed. How about the other plots (ACF/PACF)?

select between close / open / high / low candle data source (instead of only close)
Python plots (robust) as an alternative to the QT app.
Qt app compiles on latest Debian now
plot the distribution of the results obtained by the MonteCarlo method
allow various input formats and guess which one we're dealing with