diktya.random_search¶
-
fmin
(f, space_func, n=50, n_jobs='n_cpus', verbose=0)[source]¶ Minimizes
f
by using random search.Parameters: - f (function) – function to optimize. Gets output of space_func as input.
- space_func (function) – Returns random samples form the search space.
- n (int) – Number of samples to run. Default 50
- n_jobs (int|str) – Number of parallel jobs. Use
'n_cpus'` for same amount as cpus avialable. Default ``'n_cpus'
.
Simple Example:
def quadratic_function(): return (x - 2) ** 2 def space_function(): return np.random.uniform(-2, 4) results = fmin(quadratic_function, space_function, n=50) # sorted by score print("Min score: {}".format(results[0][0]))