gumbel
- hana_ml.algorithms.pal.random.gumbel(conn_context, location=0, scale=1, num_random=100, seed=None, thread_ratio=None)
Draw samples from a Gumbel distribution, which is one of a class of Generalized Extreme Value (GEV) distributions used in modeling extreme value problems.
- Parameters:
- conn_contextConnectionContext
Database connection object.
- locationfloat, optional
Defaults to 0.
- scalefloat, optional
Defaults to 1.
- num_randomint, optional
Specifies the number of random data to be generated.
Defaults to 100.
- seedint, optional
Indicates the seed used to initialize the random number generator:
0: Uses the system time.
Not 0: Uses the specified seed.
Note
When multithreading is enabled, the random number sequences of different runs might be different even if the SEED value remains the same.
Defaults to 0.
- thread_ratiofloat, optional
Adjusts the percentage of available threads to use, from 0 to 1. A value of 0 indicates the use of a single thread, while 1 implies the use of all possible current threads. Values outside the range will be ignored and this function heuristically determines the number of threads to use.
Defaults to 0.
- Returns:
- DataFrame
Dataframe containing the generated random samples.
Examples
>>> res = gumbel(conn_context=cc, location=0, scale=1, num_random=10) >>> res.collect()