TnT_Split
The TnT_Split
object provides methods for splitting datasets into testing-sets and training-sets.
Attributes
- Graph
-
- Supertypes
-
class Objecttrait Matchableclass Any
- Self type
-
TnT_Split.type
Members list
Value members
Concrete methods
Split the dataset given as a combined data-response matrix into a testing-set and training-set based on the given indices.
Split the dataset given as a combined data-response matrix into a testing-set and training-set based on the given indices.
Value parameters
- idx
-
the indices for the testing-set
- xy
-
the combined data-response matrix
Attributes
Split the dataset given as a data matrix and a response vector into a testing-set and training-set based on the given indices.
Split the dataset given as a data matrix and a response vector into a testing-set and training-set based on the given indices.
Value parameters
- idx
-
the set of indices for the testing-set
- x
-
the input/data matrix (for some models this may be null => return (null, null)
- y
-
the output/response vector
Attributes
- See also
-
scalation.modeling.Predictor
Split the dataset given as a data matrix and an integer-valued response vector into a testing-set and training-set based on the given indices.
Split the dataset given as a data matrix and an integer-valued response vector into a testing-set and training-set based on the given indices.
Value parameters
- idx
-
the indices for the testing-set
- x
-
the input/data matrix (for some models this may be null => return (null, null)
- y
-
the integer-valued output/response vector
Attributes
- See also
-
scalation.modelingq.classifying.Classifier
Split the dataset given as a data matrix and a response matrix into a testing-set and training-set based on the given indices.
Split the dataset given as a data matrix and a response matrix into a testing-set and training-set based on the given indices.
Value parameters
- idx
-
the indices for the testing-set
- x
-
the input/data matrix
- y
-
the output/response matrix
Attributes
- See also
-
scalation.modeling.neuralnet.PredictorMV
Make a permutation generator for integers from 0 until limit.
Make a permutation generator for integers from 0 until limit.
Value parameters
- limit
-
the upper limit of integers (exclusive)
- stream
-
the random number stream to use
Attributes
Return the indices for the test-set.
Return the indices for the test-set.
Value parameters
- n_test
-
the size of test-set
- rando
-
whether to select indices randomly or in blocks (defaults to true)