I’m using TuneSearchCV
to tune classifiers. Here is a snippet that I’m using-
TuneSearchCV(model,
param_distributions=config,
n_trials=200,
early_stopping=False,
max_iters=1,
search_optimization="bayesian",
n_jobs=-1,
refit=True,
cv= StratifiedKFold(n_splits=5,shuffle=True,random_state=42),
verbose=0,
#loggers = "tensorboard",
random_state=42,
local_dir="./ray_results" )
Question is: “does search_optimization
and n_jobs
go together?” in the above snippet.
The way that I interpret is n_jobs=-1
will execute all 200 trials at once and there is no use of search_optimization
parameter. So I should be using something like n_jobs=50
and hope that next batch will be picked better based on the results?
Can someone please correct my interpretation?
Thanks!