# LSTM + MLP
defaults:
  - base_model
  - loss: ic_loss
  - optimizer: adam
  - metric: q4l_default_metric
output_type: signal
basic_info:
  output_dim: 1
trainer:
  max_epochs: 100


model_type: non_dl
name: XGBoost
components:
  actual_model:
    name: XGBModel
    module_path: q4l.model.zoo.gbdt.xgboost
    kwargs:
      eval_metric: rmse
      colsample_bytree: 0.8879
      eta: 0.0421
      max_depth: 8
      n_estimators: 647
      subsample: 0.8789
      nthread: 20
