GVHD_Prediction / src /params /model_params_chronic.yaml
mfarnas
default params yaml
586d10f
CatBoost:
ensemble:
learning_rate: 0.03
depth: 6
loss_function: Logloss
random_seed: 0
l2_leaf_reg: 3
subsample: 0.9
grow_policy: Lossguide # SymmetricTree or Depthwise or Lossguide
bagging_temperature: 1
random_strength: 3
min_data_in_leaf: 25
iterations: 10000
early_stopping_rounds: 50
custom_loss: ['AUC', "F1", "Accuracy", "Precision", "Recall", "BrierScore", "Logloss"]
logging_level: 'Silent' # or 'Verbose', 'Info', 'Debug'
train_dir: '/tmp' # avoid write permission issues
auto_class_weights: Balanced # or None, or SqrtBalanced
single_model:
# in this mode, the model is trained on the entire dataset using the best_iter obtained from cross-validation
learning_rate: 0.03
depth: 6
loss_function: Logloss
random_seed: 0
l2_leaf_reg: 3
subsample: 0.9
grow_policy: Lossguide # SymmetricTree or Depthwise or Lossguide
bagging_temperature: 1
random_strength: 3
min_data_in_leaf: 25
custom_loss: ['AUC', "F1", "Accuracy", "Precision", "Recall", "BrierScore", "Logloss"]
logging_level: 'Silent' # or 'Verbose', 'Info', 'Debug'
train_dir: '/tmp' # avoid write permission issues
auto_class_weights: Balanced # or None, or SqrtBalanced