parameters_noLeak.yaml

imports:
  sklearn.linear_model :
    - ElasticNet
  sklearn.preprocessing:
    - Normalizer
  classif:
    - XdawnCovariances
    - TangentSpace
    - AddMeta
    - ElectrodeSelect
  
CrossVal:
  cores: 4
  folds: 4
  repetitions: 10
  path: results.csv
  comments: 'model-final-noLeak'

Submission:
  path: submission-noLeak.csv
  cores: 4

MetaPipeline:
  #leak:
  bagging:
     bag_size: 0.51 # % of subjects to train on in each bagged model. If bag_size==1 then LOSO bagging is performed 
     models: 500 # ignored for LOSO bagging

pipeline:
  - XdawnCovariances:
      nfilter: 5
      subelec: range(0,56,1)
  - ElectrodeSelect:
      nfilters: 5
      nelec: 35
      metric: "'riemann'"
  - TangentSpace:
      metric: "'logeuclid'"
      tsupdate: False
  - Normalizer:
      norm: '"l1"'
  - AddMeta:
  - ElasticNet:
      l1_ratio: 0.5
      alpha: 2e-4
      normalize: True