Documentation

Welcome to the developer documentation for SigOpt. If you have a question you can’t answer, feel free to contact us!
Welcome to the new SigOpt docs! If you're looking for the classic SigOpt documentation then you can find that here. Otherwise, happy optimizing!

Random Search Experiment

See the notebook below for a demonstration of how easy random search is with SigOpt.

Description

A random search experiment enables you to randomly search over your hyperparameter space with the SigOpt Platform.

sigopt.create_experiment(
  name="Random search",
  type="random",
  parameters=[
    dict(
      name="hidden_layer_size",
      type="int",
      bounds=dict(
        min=32,
        max=512
      )
    ),
    dict(
      name="activation_function",
      type="categorical",
      categorical_values=[
        "relu",
        "tanh"
      ]
    )
  ],
  metrics=[
    dict(
      name="holdout_accuracy",
      objective="maximize"
    )
  ],
  parallel_bandwidth=1,
  budget=30
)