.. _robo_gp: RoBO Gaussian Process --------------------- .. code-block:: yaml experiment: algorithms: RoBO_GP: seed: 0 n_initial_points: 20 maximizer: 'random' acquisition_func: 'log_ei' normalize_input: True normalize_output: False .. autoclass:: orion.algo.robo.gp.RoBO_GP .. _robo_gp_mcmc: RoBO Gaussian Process with MCMC ------------------------------- .. code-block:: yaml experiment: algorithms: RoBO_GP_MCMC: seed: 0 n_initial_points: 20 maximizer: 'random' acquisition_func: 'log_ei' normalize_input: True normalize_output: False chain_length: 2000 burnin_steps: 2000 .. autoclass:: orion.algo.robo.gp.RoBO_GP_MCMC :exclude-members: build_acquisition_func .. _robo_random_forest: RoBO Random Forest ------------------ .. code-block:: yaml experiment: algorithms: RoBO_RandomForest: seed: 0 n_initial_points: 20 maximizer: 'random' acquisition_func: 'log_ei' num_trees: 30 do_bootstrapping: True n_points_per_tree: 0 compute_oob_error: False return_total_variance: True .. autoclass:: orion.algo.robo.randomforest.RoBO_RandomForest :exclude-members: build_acquisition_func .. _robo_dngo: RoBO DNGO --------- .. code-block:: yaml experiment: algorithms: RoBO_DNGO: seed: 0 n_initial_points: 20 maximizer: 'random' acquisition_func: 'log_ei' normalize_input: True normalize_output: False chain_length: 2000 burnin_steps: 2000 batch_size: 10 num_epochs: 500 learning_rate: 1e-2 adapt_epoch: 5000 .. autoclass:: orion.algo.robo.dngo.RoBO_DNGO :exclude-members: build_acquisition_func .. _robo_bohamiann: RoBO BOHAMIANN -------------- .. code-block:: yaml experiment: algorithms: RoBO_BOHAMIANN: seed: 0 n_initial_points: 20 maximizer: 'random' acquisition_func: 'log_ei' normalize_input: True normalize_output: False burnin_steps: 2000 sampling_method: "adaptive_sghmc" use_double_precision: True num_steps: null keep_every: 100 learning_rate: 1e-2 batch_size: 20 epsilon: 1e-10 mdecay: 0.05 verbose: False .. autoclass:: orion.algo.robo.bohamiann.RoBO_BOHAMIANN :exclude-members: build_acquisition_func