RandomSamplingAlgorithm Class  
Random Sampling Algorithm.
Constructor
RandomSamplingAlgorithm(*, rule: str | None = None, seed: int | None = None, logbase: float | str | None = None)
		Keyword-Only Parameters
| Name | Description | 
|---|---|
| 
		 rule 
	 | 
	
		 The specific type of random algorithm. Accepted values are: "random" and "sobol". Default value: None 
			 | 
| 
		 seed 
	 | 
	
		
		 The seed for random number generation. Default value: None 
			 | 
| 
		 logbase 
	 | 
	
		
		 A positive number or the number "e" in string format to be used as the base for log based random sampling. Default value: None 
			 | 
Examples
Assigning a random sampling algorithm for a SweepJob
   from azure.ai.ml.entities import CommandJob
   from azure.ai.ml.sweep import RandomSamplingAlgorithm, SweepJob, SweepJobLimits
   command_job = CommandJob(
       inputs=dict(kernel="linear", penalty=1.0),
       compute=cpu_cluster,
       environment=f"{job_env.name}:{job_env.version}",
       code="./scripts",
       command="python scripts/train.py --kernel $kernel --penalty $penalty",
       experiment_name="sklearn-iris-flowers",
   )
   sweep = SweepJob(
       sampling_algorithm=RandomSamplingAlgorithm(seed=999, rule="sobol", logbase="e"),
       trial=command_job,
       search_space={"ss": Choice(type="choice", values=[{"space1": True}, {"space2": True}])},
       inputs={"input1": {"file": "top_level.csv", "mode": "ro_mount"}},  # type:ignore
       compute="top_level",
       limits=SweepJobLimits(trial_timeout=600),
   )