train_test.inp

####  sample input to "train_test"  ####

train_x_fn=sample/train.data.x  # Training data points
train_y_fn=sample/train.data.y  # Training targets

test_x_fn=sample/test.data.x    # Test data points
test_y_fn=sample/test.data.y    # Test targets

evaluation_fn=output/sample.evaluation  # Where to write evaluation results
  
model_fn_prefix=output/m  # Comment this out if models should not be saved


#---  training parameters
algorithm=RGF       # RGF with L2 regularization on leaf-only models
reg_L2=1            # Regularization parameter
loss=LS             # Square loss
test_interval=100   # Test (and save) models every time 100 leaves are added
max_leaf_forest=500 # Stop training when #leaf reaches 500
Verbose             # Display info during training

#---  other parameters (commented out)
#NormalizeTarget    # Normalize targets so that the average becomes zero
#train_w_fn=??             # User-specified weights of data points
#model_fn_for_warmstart=?? # Path to the model file to do warm-start with