Sample Weight assigns weight to input sample. Weight may be specified by
input param class_weight
or sample_weight_name
. Output data
instances will each have a weight value, which will be used for
training. While weighted instances may be used for
prediction(SampleWeight component will assign weights to instances if
prediction pipeline includes this component), Evaluation currently does
not take weights into account when calculating metrics.
If result weighted instances include negative weight, a warning message will be given.
Please note that when weight is not None, only weight_diff
convergence
check method may be used for training GLM.
:exclamation:
If both `class_weight` and `sample_weight_name` are provided, values
from column of `sample_weight_name` will be used.