PHOTONAI WIZARD

Design your pipeline

Analysis Name

Specify a name for this analysis.

Project Description

Please provide a short description of your project.

Project Folder

Please give a local directory for your photon analysis

Design Choices

You optimize for mean_absolute_error using random_grid_search.

Optimizer	random_grid_search	n_configurations: 30
Inner Cross Validation Strategy	KFold	n_splits: 3 \|shuffle: True
Metrics	mean_squared_error
	mean_absolute_error
	explained_variance
Best Config Metric	mean_absolute_error

Transformers

Your pipeline contains 2 transformer elements specifying 4 hyperparameters.

SimpleImputer	missing_values	np.nan
	strategy	mean
	fill_value	0
PCA	n_components	0.8

Estimators

Your learning algorithm is RandomForestRegressor with 5 hyperparameters.

RandomForestRegressor	n_estimators	50
	criterion	mse
	max_depth	None
	min_samples_split	2
	min_samples_leaf	1

                        
                            
# Specify how results are going to be saved
# Define hyperpipe
hyperpipe = Hyperpipe('None',
                      project_folder = './results',
                      optimizer="random_grid_search",
                      optimizer_params={'n_configurations': 30},
                      metrics=['mean_squared_error', 'mean_absolute_error', 'explained_variance'],
                      best_config_metric="mean_absolute_error",
                      use_test_set=False,
                      inner_cv = KFold(n_splits=3, shuffle=True))
        
# Add transformer elements
hyperpipe += PipelineElement("SimpleImputer", hyperparameters={}, 
                             test_disabled=False, missing_values=np.nan, strategy='mean', fill_value=0)
hyperpipe += PipelineElement("PCA", hyperparameters={}, 
                             test_disabled=False, n_components=0.8)
hyperpipe += PipelineElement("RandomForestRegressor", hyperparameters={}, n_estimators=50, criterion='mse', max_depth=None, min_samples_split=2, min_samples_leaf=1)

PHOTONAI Wizard