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!

Grid Search Experiment

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

Description

A grid search experiment enables users to execute an exhaustive search on a user-defined grid with the SigOpt Platform. This means that you'll need to assign grid (or categorical) values to every parameter as part of the experiment create call.

sigopt.create_experiment(
  name="Grid search",
  type="grid",
  parameters=[
    dict(
      name="hidden_layer_size",
      type="int",
      grid=[
        32,
        64,
        128,
        256,
        512
      ]
    ),
    dict(
      name="activation_function",
      type="categorical",
      categorical_values=[
        "relu",
        "tanh"
      ]
    )
  ],
  metrics=[
    dict(
      name="holdout_accuracy",
      objective="maximize"
    )
  ],
  parallel_bandwidth=1,
  budget=30
)