Update README.md

README.md

@@ -52,12 +52,4 @@ Once the data has been epoched it is sent for feature extraction, there is a gen
 
 Finally a passable, customisable sklearn or tensorflow classifier can be giving to the bci class, once a defined number of epochs have been obtained for each received epoch/marker type the classifier can begin to fit the model. It's advised to use bci.ReceivedMarkerCount() to get the number of received training epochs received, once the min num epochs received of each type is >= pybci.minimumEpochsRequired (default 10 of each epoch) the model will begin to fit. Once fit the classifier info can be queried with CurrentClassifierInfo, this returns the model used and accuracy, is met or number of epochs TestMode() can be called. Once in test mode you can query (sould change function to own function and queue for quering testthread) what pybci estimates the current bci epoch is(typically bseline is used for no state). [Review the examples for sklearn and model implementations](https://pybci.readthedocs.io/en/latest/BackgroundInformation/Examples.html).
 
-## ToDo!
-- Test and likely Fix multimodal after new data thread creation
-- fix psuedo plotter, when gui inactive for long period seems to crash plotter when reactivated, LSL data is still generated and button remain active though.
-- I think first stable release after the two above are done?
-- ~~Run benchmark tests on DataReceiverThread.py and AsynDataReceiverThread.py, seeking potential optimisations.~~ (Added universal optimised thread to handle all cases)
-- ~~Levels of print debug (info, error, none, timing)~~
-- ~~Retrieve feature data~~
-
-## Curently in Beta, come back in a few days for updates!
+## Any issues, recommendations, pull-requests and suggestions are welcome and encouraged!