Check parameter instantiation

[alperyeg]

In the optimizer the parameter naming is not standardized due to the namedtuple parameters and the class arguments. There should be an easier way to create parameters.

[alperyeg]

Optimizer Parameters

Crossentropy

• pop_size
• rho: elite fraction
• smoothing: scalar for the distribution
• temp_decay: decay factor
• n_iteration: number of iterations to perform
• distribution: function
• stop_criterion
• seed

Evolution

• seed
• popsize
• CXPB: crossover probability
• MUTPB: mutation probability
• NGEN: number of generations
• indpb: probability of mutation of each element in individual
• tournsize: size of the tournament
• matepar: blending two values during mating

EvolutionStrategies

• learning_rate
• noise_std
• mirrored_sampling_enabled
• fitness_shaping_enabled
• pop_size
• n_iteration
• stop_criterion
• seed

FACE

• min_pop_size
• max_pop_size
• n_elite
• smoothing
• temp_decay
• n_iteration
• distribution
• stop_criterion
• n_expand: amount by which the sample size is increased

Gradient Descent

Classic GD

• learning_rate
• exploration_step_size: standard deviation of random steps used
• n_random_steps: amount of random steps used to estimate gradient
• n_iteration
• stop_criterion

Stochastic GD

• learning_rate
• stochastic_deviation: standard deviation of the random vector used to perturbate the gradient
• stochastic_decay: decay of the influence of the random vector that is added to the gradient
• exploration_step_size
• n_random_steps
• n_iteration
• stop_criterion

Adam

• learning_rate
• exploration_step_size
• n_random_steps
• first_order_decay: amount of decay of the historic first order momentum per gradient descent step
• second_order_decay: amount of decay of the historic second order momentum per gradient descent step
• n_iteration
• stop_criterion

RMSPROP

• learning_rate
• exploration_step_size
• n_random_steps
• momentum_decay
• n_iteration
• stop_criterion
• seed

Gridsearch

• param_grid: (lower_bound, higher_bound, n_steps)

NaturalEvolutionStrategies

• learning_rate_mu
• learning_rate_sigma
• mu
• sigma
• mirrored_sampling_enabled
• fitness_shaping_enabled
• pop_size
• n_iteration
• stop_criterion
• seed

ParallelTempering

• n_parallel_runs: parallel Simulated Annealing runs
• noisy_step: size of the random step
• decay_parameters
• n_iteration
• stop_criterion
• seed
• cooling_schedules
• temperature_bounds

SimulatedAnnealing

• n_parallel_runs
• noisy_step
• temp_decay
• n_iteration
• stop_criterion
• seed
• cooling_schedule