###Planned features
- update core FEM functions to have a consistent API
- improved topomap plotting
- FEM tutorial
- improve statistical testing using prevalence inference, addressing problems of t-testing on MVPA data (Allefeld, C., Görgen, K., & Haynes, J.-D. (2016). Valid population inference for information-based imaging: From the second-level t-test to prevalence inference. NeuroImage, 141, 378–392.)
- implement cluster based permutation for topomaps over time (not just space)
- allow oversampling of trigger values within a class (under consideration)
- enable correlation of distance to boundary scores with reaction time, confidence etc.
- look into regularization
- look into better whitening / noise normalization for FEMs
###V1.0.0 is the current version
###Implemented prior to V1.0.0
- whitening (by default on for FEMs, not for BDMs as these use LDA)
- better implementation of class balancing using ADASYN to oversample (Haibo He, Yang Bai, Garcia, E. A., & Shutao Li. (2008). ADASYN: Adaptive synthetic sampling approach for imbalanced learning (pp. 1322–1328). Presented at the 2008 IEEE International Joint Conference on Neural Networks (IJCNN 2008 - Hong Kong), IEEE.)
- implemented AUC (Area Under the Curve) as the default performance measure (on top of balanced accuracy, d' and hr-far).
- updated all core BDM functions to have a (more or less) consistent API
- all core functions are now pre-pended with adam_
- BDM tutorial (1st level, 2nd level, plotting) with example data