validate

smile.validation.`package`.validate
object validate

Attributes

Graph
Supertypes
class Object
trait Matchable
class Any
Self type
validate.type

Members list

Value members

Concrete methods

def classification[T <: AnyRef, M <: Classifier[T]](x: Array[T], y: Array[Int], testx: Array[T], testy: Array[Int])(trainer: (Array[T], Array[Int]) => M): ClassificationValidation[M]

Test a generic classifier. The accuracy will be measured and printed out on standard output.

Test a generic classifier. The accuracy will be measured and printed out on standard output.

Type parameters

T

the type of training and test data.

Value parameters

testx

test data.

testy

test data labels.

trainer

a code block to return a classifier trained on the given data.

x

training data.

y

training labels.

Attributes

Returns

the trained classifier.

def classification[M <: DataFrameClassifier](formula: Formula, train: DataFrame, test: DataFrame)(trainer: (Formula, DataFrame) => M): ClassificationValidation[M]

Test a generic classifier. The accuracy will be measured and printed out on standard output.

Test a generic classifier. The accuracy will be measured and printed out on standard output.

Value parameters

test

test data.

train

training data.

trainer

a code block to return a classifier trained on the given data.

Attributes

Returns

the trained classifier.

def regression[T <: AnyRef, M <: Regression[T]](x: Array[T], y: Array[Double], testx: Array[T], testy: Array[Double])(trainer: (Array[T], Array[Double]) => M): RegressionValidation[M]

Test a generic classifier. The accuracy will be measured and printed out on standard output.

Test a generic classifier. The accuracy will be measured and printed out on standard output.

Type parameters

T

the type of training and test data.

Value parameters

testx

test data.

testy

test data labels.

trainer

a code block to return a classifier trained on the given data.

x

training data.

y

training labels.

Attributes

Returns

the trained classifier.

def regression[M <: DataFrameRegression](formula: Formula, train: DataFrame, test: DataFrame)(trainer: (Formula, DataFrame) => M): RegressionValidation[M]

Test a generic classifier. The accuracy will be measured and printed out on standard output.

Test a generic classifier. The accuracy will be measured and printed out on standard output.

Value parameters

test

test data.

train

training data.

trainer

a code block to return a classifier trained on the given data.

Attributes

Returns

the trained classifier.