Random Search Experiment

Description

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

View a sample random search experiment implementation in a notebook

See this notebook for a demonstration of how easy random search is with SigOpt. For more notebook instructions and tutorials, check out our GitHub notebook tutorials repo.
Python
YAML
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
)
name: Random search
type: random
parameters:
- name: hidden_layer_size
type: int
bounds:
min: 32
max: 512
- name: activation_function
type: categorical
categorical_values:
- relu
- tanh
metrics:
- name: holdout_accuracy
objective: maximize
parallel_bandwidth: 1
budget: 30
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