- 0.61.0 (latest)
- 0.60.0
- 0.59.0
- 0.58.0
- 0.57.0
- 0.56.0
- 0.55.0
- 0.54.0
- 0.53.0
- 0.52.0
- 0.51.0
- 0.50.0
- 0.49.0
- 0.48.0
- 0.47.0
- 0.46.0
- 0.45.0
- 0.44.0
- 0.43.0
- 0.42.0
- 0.41.0
- 0.40.0
- 0.39.0
- 0.38.0
- 0.37.0
- 0.36.0
- 0.35.0
- 0.34.0
- 0.33.0
- 0.32.0
- 0.31.0
- 0.30.0
- 0.29.0
- 0.28.0
- 0.27.0
- 0.26.0
- 0.25.0
- 0.24.0
- 0.23.0
- 0.22.0
- 0.21.0
- 0.20.0
- 0.19.0
- 0.18.0
- 0.17.0
- 0.16.0
- 0.15.0
- 0.14.0
- 0.13.0
- 0.12.0
- 0.11.0
- 0.10.0
- 0.9.1
- 0.8.0
- 0.7.0
- 0.6.0
- 0.5.0
- 0.4.0
- 0.3.0
- 0.2.0
- 0.1.0
Reference documentation and code samples for the Vertex AI V1 API class Google::Cloud::AIPlatform::V1::FractionSplit.
Assigns the input data to training, validation, and test sets as per the
given fractions. Any of training_fraction
, validation_fraction
and
test_fraction
may optionally be provided, they must sum to up to 1. If the
provided ones sum to less than 1, the remainder is assigned to sets as
decided by Vertex AI. If none of the fractions are set, by default roughly
80% of data is used for training, 10% for validation, and 10% for test.
Inherits
- Object
Extended By
- Google::Protobuf::MessageExts::ClassMethods
Includes
- Google::Protobuf::MessageExts
Methods
#test_fraction
def test_fraction() -> ::Float
- (::Float) — The fraction of the input data that is to be used to evaluate the Model.
#test_fraction=
def test_fraction=(value) -> ::Float
- value (::Float) — The fraction of the input data that is to be used to evaluate the Model.
- (::Float) — The fraction of the input data that is to be used to evaluate the Model.
#training_fraction
def training_fraction() -> ::Float
- (::Float) — The fraction of the input data that is to be used to train the Model.
#training_fraction=
def training_fraction=(value) -> ::Float
- value (::Float) — The fraction of the input data that is to be used to train the Model.
- (::Float) — The fraction of the input data that is to be used to train the Model.
#validation_fraction
def validation_fraction() -> ::Float
- (::Float) — The fraction of the input data that is to be used to validate the Model.
#validation_fraction=
def validation_fraction=(value) -> ::Float
- value (::Float) — The fraction of the input data that is to be used to validate the Model.
- (::Float) — The fraction of the input data that is to be used to validate the Model.