Documentation
Welcome to the developer documentation for SigOpt. If you have a question you can’t answer, feel free to contact us!Normal Prior Object
Normal Prior for a parameter prior belief.
Fields
Key | Type | Value |
---|---|---|
mean | float | Mean of the truncated Normal distribution. |
name | string | normal |
scale | float | Standard deviation of the truncated Normal distribution. |
Example
{
"mean": 0.5,
"name": "normal",
"object": "normal_prior",
"scale": 1.2
}
- Multimetric Experiments
- Interpret Multimetric Experiment Solutions
- Metric Thresholds
- Metric Constraints
- Metric Strategy
- Metric Failures
- Multisolution Experiments
- Parameter Constraints
- Prior Beliefs
- Parameter Transformation
- Run in Parallel
- Tracking Suggestion and Observation Using Metadata
- Conditional Experiments (Beta)
- Multitask Experiments (Alpha)
- Training Monitor (Alpha)
- Training Monitor Visualizations (Alpha)
- Assignments
- Best Assignments
- Beta Prior
- Bounds
- Categorical Value
- Checkpoint
- Client
- Conditional
- Conditions
- Constraint Term
- Experiment
- Metadata
- Metric
- Metric Evaluation
- Metric Importances
- Normal Prior
- Observation
- Organization
- Pagination
- Parameter
- Parameter Constraint
- Plan
- Plan Period
- Plan Rules
- Prior
- Progress
- Project
- Queued Suggestion
- Session
- Stopping Criteria
- Suggestion
- Token
- Training Run
- User
SigOpt OrchestrateAlpha
Training RunsBeta
API Topics
Advanced Features